CINXE.COM

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Search results for: energy allocation method</title> <meta name="description" content="Search results for: energy allocation method"> <meta name="keywords" content="energy allocation method"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="energy allocation method" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="energy allocation method"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 25853</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: energy allocation method</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25853</span> A Succinct Method for Allocation of Reactive Power Loss in Deregulated Scenario</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20S.%20Savier">J. S. Savier</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Real power is the component power which is converted into useful energy whereas reactive power is the component of power which cannot be converted to useful energy but it is required for the magnetization of various electrical machineries. If the reactive power is compensated at the consumer end, the need for reactive power flow from generators to the load can be avoided and hence the overall power loss can be reduced. In this scenario, this paper presents a succinct method called JSS method for allocation of reactive power losses to consumers connected to radial distribution networks in a deregulated environment. The proposed method has the advantage that no assumptions are made while deriving the reactive power loss allocation method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deregulation" title="deregulation">deregulation</a>, <a href="https://publications.waset.org/abstracts/search?q=reactive%20power%20loss%20allocation" title=" reactive power loss allocation"> reactive power loss allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20distribution%20systems" title=" radial distribution systems"> radial distribution systems</a>, <a href="https://publications.waset.org/abstracts/search?q=succinct%20method" title=" succinct method"> succinct method</a> </p> <a href="https://publications.waset.org/abstracts/47667/a-succinct-method-for-allocation-of-reactive-power-loss-in-deregulated-scenario" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47667.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">376</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25852</span> Loss Allocation in Radial Distribution Networks for Loads of Composite Types</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sumit%20Banerjee">Sumit Banerjee</a>, <a href="https://publications.waset.org/abstracts/search?q=Chandan%20Kumar%20Chanda"> Chandan Kumar Chanda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper presents allocation of active power losses and energy losses to consumers connected to radial distribution networks in a deregulated environment for loads of composite types. A detailed comparison among four algorithms, namely quadratic loss allocation, proportional loss allocation, pro rata loss allocation and exact loss allocation methods are presented. Quadratic and proportional loss allocations are based on identifying the active and reactive components of current in each branch and the losses are allocated to each consumer, pro rata loss allocation method is based on the load demand of each consumer and exact loss allocation method is based on the actual contribution of active power loss by each consumer. The effectiveness of the proposed comparison among four algorithms for composite load is demonstrated through an example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=composite%20type" title="composite type">composite type</a>, <a href="https://publications.waset.org/abstracts/search?q=deregulation" title=" deregulation"> deregulation</a>, <a href="https://publications.waset.org/abstracts/search?q=loss%20allocation" title=" loss allocation"> loss allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20distribution%20networks" title=" radial distribution networks"> radial distribution networks</a> </p> <a href="https://publications.waset.org/abstracts/42700/loss-allocation-in-radial-distribution-networks-for-loads-of-composite-types" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42700.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">286</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25851</span> A New Reliability Allocation Method Based on Fuzzy Numbers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Peng%20Li">Peng Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Chuanri%20Li"> Chuanri Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Tao%20Li"> Tao Li </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Reliability allocation is quite important during early design and development stages for a system to apportion its specified reliability goal to subsystems. This paper improves the reliability fuzzy allocation method and gives concrete processes on determining the factor set, the factor weight set, judgment set, and multi-grade fuzzy comprehensive evaluation. To determine the weight of factor set, the modified trapezoidal numbers are proposed to reduce errors caused by subjective factors. To decrease the fuzziness in the fuzzy division, an approximation method based on linear programming is employed. To compute the explicit values of fuzzy numbers, centroid method of defuzzification is considered. An example is provided to illustrate the application of the proposed reliability allocation method based on fuzzy arithmetic. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reliability%20allocation" title="reliability allocation">reliability allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20arithmetic" title=" fuzzy arithmetic"> fuzzy arithmetic</a>, <a href="https://publications.waset.org/abstracts/search?q=allocation%20weight" title=" allocation weight"> allocation weight</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20programming" title=" linear programming "> linear programming </a> </p> <a href="https://publications.waset.org/abstracts/27101/a-new-reliability-allocation-method-based-on-fuzzy-numbers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27101.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">342</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25850</span> Operation Strategy of Multi-Energy Storage System Considering Power System Reliability </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wook-Won%20Kim">Wook-Won Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Je-Seok%20Shin"> Je-Seok Shin</a>, <a href="https://publications.waset.org/abstracts/search?q=Jin-O%20Kim"> Jin-O Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As the penetration of Energy Storage System (ESS) increases in the power system due to higher performance and lower cost than ever, ESS is expanding its role to the ancillary service as well as the storage of extra energy from the intermittent renewable energy resources. For multi-ESS with different capacity and SOC level each other, it is required to make the optimal schedule of SOC level use the multi-ESS effectively. This paper proposes the energy allocation method for the multiple battery ESS with reliability constraint, in order to make the ESS discharge the required energy as long as possible. A simple but effective method is proposed in this paper, to satisfy the power for the spinning reserve requirement while improving the system reliability. Modelling of ESS is also proposed, and reliability is evaluated by using the combined reliability model which includes the proposed ESS model and conventional generation one. In the case study, it can be observed that the required power is distributed to each ESS adequately and accordingly, the SOC is scheduled to improve the reliability indices such as Loss of Load Probability (LOLP) and Loss of Load Expectation (LOLE). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multiple%20energy%20storage%20system%20%28MESS%29" title="multiple energy storage system (MESS)">multiple energy storage system (MESS)</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method" title=" energy allocation method"> energy allocation method</a>, <a href="https://publications.waset.org/abstracts/search?q=SOC%20schedule" title=" SOC schedule"> SOC schedule</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability%20constraints" title=" reliability constraints"> reliability constraints</a> </p> <a href="https://publications.waset.org/abstracts/48673/operation-strategy-of-multi-energy-storage-system-considering-power-system-reliability" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48673.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">368</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25849</span> A New Method to Winner Determination for Economic Resource Allocation in Cloud Computing Systems </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ebrahim%20Behrouzian%20Nejad">Ebrahim Behrouzian Nejad</a>, <a href="https://publications.waset.org/abstracts/search?q=Rezvan%20Alipoor%20Sabzevari"> Rezvan Alipoor Sabzevari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cloud computing systems are large-scale distributed systems, so that they focus more on large scale resource sharing, cooperation of several organizations and their use in new applications. One of the main challenges in this realm is resource allocation. There are many different ways to resource allocation in cloud computing. One of the common methods to resource allocation are economic methods. Among these methods, the auction-based method has greater prominence compared with Fixed-Price method. The double combinatorial auction is one of the proper ways of resource allocation in cloud computing. This method includes two phases: winner determination and resource allocation. In this paper a new method has been presented to determine winner in double combinatorial auction-based resource allocation using Imperialist Competitive Algorithm (ICA). The experimental results show that in our new proposed the number of winner users is higher than genetic algorithm. On other hand, in proposed algorithm, the number of winner providers is higher in genetic algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title="cloud computing">cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20allocation" title=" resource allocation"> resource allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=double%20auction" title=" double auction"> double auction</a>, <a href="https://publications.waset.org/abstracts/search?q=winner%20determination" title=" winner determination "> winner determination </a> </p> <a href="https://publications.waset.org/abstracts/35920/a-new-method-to-winner-determination-for-economic-resource-allocation-in-cloud-computing-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35920.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">359</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25848</span> Exploring SSD Suitable Allocation Schemes Incompliance with Workload Patterns</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jae%20Young%20Park">Jae Young Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Hwansu%20Jung"> Hwansu Jung</a>, <a href="https://publications.waset.org/abstracts/search?q=Jong%20Tae%20Kim"> Jong Tae Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Whether the data has been well parallelized is an important factor in the Solid-State-Drive (SSD) performance. SSD parallelization is affected by allocation scheme and it is directly connected to SSD performance. There are dynamic allocation and static allocation in representative allocation schemes. Dynamic allocation is more adaptive in exploiting write operation parallelism, while static allocation is better in read operation parallelism. Therefore, it is hard to select the appropriate allocation scheme when the workload is mixed read and write operations. We simulated conditions on a few mixed data patterns and analyzed the results to help the right choice for better performance. As the results, if data arrival interval is long enough prior operations to be finished and continuous read intensive data environment static allocation is more suitable. Dynamic allocation performs the best on write performance and random data patterns. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20allocation" title="dynamic allocation">dynamic allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=NAND%20flash%20based%20SSD" title=" NAND flash based SSD"> NAND flash based SSD</a>, <a href="https://publications.waset.org/abstracts/search?q=SSD%20parallelism" title=" SSD parallelism"> SSD parallelism</a>, <a href="https://publications.waset.org/abstracts/search?q=static%20allocation" title=" static allocation"> static allocation</a> </p> <a href="https://publications.waset.org/abstracts/41931/exploring-ssd-suitable-allocation-schemes-incompliance-with-workload-patterns" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41931.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">339</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25847</span> A Cognitive Approach to the Optimization of Power Distribution across an Educational Campus</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mrinmoy%20Majumder">Mrinmoy Majumder</a>, <a href="https://publications.waset.org/abstracts/search?q=Apu%20Kumar%20Saha"> Apu Kumar Saha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The ever-increasing human population and its demand for energy is placing stress upon conventional energy sources; and as demand for power continues to outstrip supply, the need to optimize energy distribution and utilization is emerging as an important focus for various stakeholders. The distribution of available energy must be achieved in such a way that the needs of the consumer are satisfied. However, if the availability of resources is not sufficient to satisfy consumer demand, it is necessary to find a method to select consumers based on factors such as their socio-economic or environmental impacts. Weighting consumer types in this way can help separate them based on their relative importance, and cognitive optimization of the allocation process can then be carried out so that, even on days of particularly scarce supply, the socio-economic impacts of not satisfying the needs of consumers can be minimized. In this context, the present study utilized fuzzy logic to assign weightage to different types of consumers based at an educational campus in India, and then established optimal allocation by applying the non-linear mapping capability of neuro-genetic algorithms. The outputs of the algorithms were compared with similar outputs from particle swarm optimization and differential evolution algorithms. The results of the study demonstrate an option for the optimal utilization of available energy based on the socio-economic importance of consumers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=power%20allocation" title="power allocation">power allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20problem" title=" optimization problem"> optimization problem</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=environmental%20and%20ecological%20engineering" title=" environmental and ecological engineering"> environmental and ecological engineering</a> </p> <a href="https://publications.waset.org/abstracts/19462/a-cognitive-approach-to-the-optimization-of-power-distribution-across-an-educational-campus" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19462.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">479</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25846</span> Optimal Sizes of Energy Storage for Economic Operation Management</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rohalla%20Moghimi">Rohalla Moghimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sirus%20Mohammadi"> Sirus Mohammadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Batteries for storage of electricity from solar and wind generation farms are a key element in the success of sustainability. In recent years, due to large integration of Renewable Energy Sources (RESs) like wind turbine and photovoltaic unit into the Micro-Grid (MG), the necessity of Battery Energy Storage (BES) has increased dramatically. The BES has several benefits and advantages in the MG-based applications such as short term power supply, power quality improvement, facilitating integration of RES, ancillary service and arbitrage. This paper presents the cost-based formulation to determine the optimal size of the BES in the operation management of MG. Also, some restrictions, i.e. power capacity of Distributed Generators (DGs), power and energy capacity of BES, charge/discharge efficiency of BES, operating reserve and load demand satisfaction should be considered as well. In this paper, a methodology is proposed for the optimal allocation and economic analysis of ESS in MGs on the basis of net present value (NPV). As the optimal operation of an MG strongly depends on the arrangement and allocation of its ESS, economic operation strategies and optimal allocation methods of the ESS devices are required for the MG. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microgrid" title="microgrid">microgrid</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20storage%20system" title=" energy storage system"> energy storage system</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20sizing" title=" optimal sizing"> optimal sizing</a>, <a href="https://publications.waset.org/abstracts/search?q=net%20present%20value" title=" net present value"> net present value</a> </p> <a href="https://publications.waset.org/abstracts/19067/optimal-sizes-of-energy-storage-for-economic-operation-management" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19067.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">556</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25845</span> Energy Efficient Resource Allocation and Scheduling in Cloud Computing Platform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shuen-Tai%20Wang">Shuen-Tai Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Ying-Chuan%20Chen"> Ying-Chuan Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu-Ching%20Lin"> Yu-Ching Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There has been renewal of interest in the relation between Green IT and cloud computing in recent years. Cloud computing has to be a highly elastic environment which provides stable services to users. The growing use of cloud computing facilities has caused marked energy consumption, putting negative pressure on electricity cost of computing center or data center. Each year more and more network devices, storages and computers are purchased and put to use, but it is not just the number of computers that is driving energy consumption upward. We could foresee that the power consumption of cloud computing facilities will double, triple, or even more in the next decade. This paper aims at resource allocation and scheduling technologies that are short of or have not well developed yet to reduce energy utilization in cloud computing platform. In particular, our approach relies on recalling services dynamically onto appropriate amount of the machines according to user’s requirement and temporarily shutting down the machines after finish in order to conserve energy. We present initial work on integration of resource and power management system that focuses on reducing power consumption such that they suffice for meeting the minimizing quality of service required by the cloud computing platform. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title="cloud computing">cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20utilization" title=" energy utilization"> energy utilization</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20consumption" title=" power consumption"> power consumption</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20allocation" title=" resource allocation"> resource allocation</a> </p> <a href="https://publications.waset.org/abstracts/55519/energy-efficient-resource-allocation-and-scheduling-in-cloud-computing-platform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55519.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">339</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25844</span> Energy Management Method in DC Microgrid Based on the Equivalent Hydrogen Consumption Minimum Strategy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ying%20Han">Ying Han</a>, <a href="https://publications.waset.org/abstracts/search?q=Weirong%20Chen"> Weirong Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Qi%20Li"> Qi Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An energy management method based on equivalent hydrogen consumption minimum strategy is proposed in this paper aiming at the direct-current (DC) microgrid consisting of photovoltaic cells, fuel cells, energy storage devices, converters and DC loads. The rational allocation of fuel cells and battery devices is achieved by adopting equivalent minimum hydrogen consumption strategy with the full use of power generated by photovoltaic cells. Considering the balance of the battery’s state of charge (SOC), the optimal power of the battery under different SOC conditions is obtained and the reference output power of the fuel cell is calculated. And then a droop control method based on time-varying droop coefficient is proposed to realize the automatic charge and discharge control of the battery, balance the system power and maintain the bus voltage. The proposed control strategy is verified by RT-LAB hardware-in-the-loop simulation platform. The simulation results show that the designed control algorithm can realize the rational allocation of DC micro-grid energy and improve the stability of system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DC%20microgrid" title="DC microgrid">DC microgrid</a>, <a href="https://publications.waset.org/abstracts/search?q=equivalent%20minimum%20hydrogen%20consumption%20strategy" title=" equivalent minimum hydrogen consumption strategy"> equivalent minimum hydrogen consumption strategy</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20management" title=" energy management"> energy management</a>, <a href="https://publications.waset.org/abstracts/search?q=time-varying%20droop%20coefficient" title=" time-varying droop coefficient"> time-varying droop coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=droop%20control" title=" droop control"> droop control</a> </p> <a href="https://publications.waset.org/abstracts/64086/energy-management-method-in-dc-microgrid-based-on-the-equivalent-hydrogen-consumption-minimum-strategy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64086.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">303</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25843</span> Systematic Approach for Energy-Supply-Orientated Production Planning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=F.%20Keller">F. Keller</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20Reinhart"> G. Reinhart</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The efficient and economic allocation of resources is one main goal in the field of production planning and control. Nowadays, a new variable gains in importance throughout the planning process: Energy. Energy-efficiency has already been widely discussed in literature, but with a strong focus on reducing the overall amount of energy used in production. This paper provides a brief systematic approach, how energy-supply-orientation can be used for an energy-cost-efficient production planning and thus combining the idea of energy-efficiency and energy-flexibility. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=production%20planning" title="production planning">production planning</a>, <a href="https://publications.waset.org/abstracts/search?q=production%20control" title=" production control"> production control</a>, <a href="https://publications.waset.org/abstracts/search?q=energy-efficiency" title=" energy-efficiency"> energy-efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=energy-flexibility" title=" energy-flexibility"> energy-flexibility</a>, <a href="https://publications.waset.org/abstracts/search?q=energy-supply" title=" energy-supply"> energy-supply</a> </p> <a href="https://publications.waset.org/abstracts/26038/systematic-approach-for-energy-supply-orientated-production-planning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26038.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">648</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25842</span> Optimal Sizes of Battery Energy Storage Systems for Economic Operation in Microgrid</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sirus%20Mohammadi">Sirus Mohammadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sara%20Ansari"> Sara Ansari</a>, <a href="https://publications.waset.org/abstracts/search?q=Darush%20dehghan"> Darush dehghan</a>, <a href="https://publications.waset.org/abstracts/search?q=Habib%20Hoshyari"> Habib Hoshyari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Batteries for storage of electricity from solar and wind generation farms are a key element in the success of sustainability. In recent years, due to large integration of Renewable Energy Sources (RESs) like wind turbine and photovoltaic unit into the Micro-Grid (MG), the necessity of Battery Energy Storage (BES) has increased dramatically. The BES has several benefits and advantages in the MG-based applications such as short term power supply, power quality improvement, facilitating integration of RES, ancillary service and arbitrage. This paper presents the cost-based formulation to determine the optimal size of the BES in the operation management of MG. Also, some restrictions, i.e. power capacity of Distributed Generators (DGs), power and energy capacity of BES, charge/discharge efficiency of BES, operating reserve and load demand satisfaction should be considered as well. In this paper, a methodology is proposed for the optimal allocation and economic analysis of ESS in MGs on the basis of net present value (NPV). As the optimal operation of an MG strongly depends on the arrangement and allocation of its ESS, economic operation strategies and optimal allocation methods of the ESS devices are required for the MG. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microgrid" title="microgrid">microgrid</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20storage%20system" title=" energy storage system"> energy storage system</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20sizing" title=" optimal sizing"> optimal sizing</a>, <a href="https://publications.waset.org/abstracts/search?q=net%20present%20value" title=" net present value"> net present value</a> </p> <a href="https://publications.waset.org/abstracts/14316/optimal-sizes-of-battery-energy-storage-systems-for-economic-operation-in-microgrid" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14316.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">494</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25841</span> Mobile Agents-Based Framework for Dynamic Resource Allocation in Cloud Computing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Safia%20Rabaaoui">Safia Rabaaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=H%C3%A9la%20Hachicha"> Héla Hachicha</a>, <a href="https://publications.waset.org/abstracts/search?q=Ezzeddine%20Zagrouba"> Ezzeddine Zagrouba</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, cloud computing is becoming the more popular technology to various companies and consumers, which benefit from its increased efficiency, cost optimization, data security, unlimited storage capacity, etc. One of the biggest challenges of cloud computing is resource allocation. Its efficiency directly influences the performance of the whole cloud environment. Finding an effective method to address these critical issues and increase cloud performance was necessary. This paper proposes a mobile agents-based framework for dynamic resource allocation in cloud computing to minimize both the cost of using virtual machines and the makespan. Furthermore, its impact on the best response time and power consumption has been studied. The simulation showed that our method gave better results than here. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title="cloud computing">cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent%20system" title=" multi-agent system"> multi-agent system</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20agent" title=" mobile agent"> mobile agent</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20resource%20allocation" title=" dynamic resource allocation"> dynamic resource allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=cost" title=" cost"> cost</a>, <a href="https://publications.waset.org/abstracts/search?q=makespan" title=" makespan"> makespan</a> </p> <a href="https://publications.waset.org/abstracts/168460/mobile-agents-based-framework-for-dynamic-resource-allocation-in-cloud-computing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168460.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">103</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25840</span> Understanding the Nature of Capital Allocation Problem in Corporate Finance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Meltem%20Gurunlu">Meltem Gurunlu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the central problems in corporate finance is the allocation of funds. This usually takes two forms: allocation of funds across firms in an economy or allocation of funds across projects or business units within a firm. The first one is typically related to the external markets (the bond market, the stock market, banks and finance companies) whereas the second form of the capital allocation is related to the internal capital markets in which corporate headquarters allocate capital to their business units. (within-group transfers, within-group credit markets, and within-group equity market). The main aim of this study is to investigate the nature of capital allocation dynamics by comparing the relevant studies carried out on external and internal capital markets with paying special significance to the business groups. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=internal%20capital%20markets" title="internal capital markets">internal capital markets</a>, <a href="https://publications.waset.org/abstracts/search?q=external%20capital%20markets" title=" external capital markets"> external capital markets</a>, <a href="https://publications.waset.org/abstracts/search?q=capital%20structure" title=" capital structure"> capital structure</a>, <a href="https://publications.waset.org/abstracts/search?q=capital%20allocation" title=" capital allocation"> capital allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=business%20groups" title=" business groups"> business groups</a>, <a href="https://publications.waset.org/abstracts/search?q=corporate%20finance" title=" corporate finance"> corporate finance</a> </p> <a href="https://publications.waset.org/abstracts/89423/understanding-the-nature-of-capital-allocation-problem-in-corporate-finance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/89423.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">195</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25839</span> Trajectory Design and Power Allocation for Energy -Efficient UAV Communication Based on Deep Reinforcement Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yuling%20Cui">Yuling Cui</a>, <a href="https://publications.waset.org/abstracts/search?q=Danhao%20Deng"> Danhao Deng</a>, <a href="https://publications.waset.org/abstracts/search?q=Chaowei%20Wang"> Chaowei Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Weidong%20Wang"> Weidong Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, unmanned aerial vehicles (UAVs) have been widely used in wireless communication, attracting more and more attention from researchers. UAVs can not only serve as a relay for auxiliary communication but also serve as an aerial base station for ground users (GUs). However, limited energy means that they cannot work all the time and cover a limited range of services. In this paper, we investigate 2D UAV trajectory design and power allocation in order to maximize the UAV's service time and downlink throughput. Based on deep reinforcement learning, we propose a depth deterministic strategy gradient algorithm for trajectory design and power distribution (TDPA-DDPG) to solve the energy-efficient and communication service quality problem. The simulation results show that TDPA-DDPG can extend the service time of UAV as much as possible, improve the communication service quality, and realize the maximization of downlink throughput, which is significantly improved compared with existing methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=UAV%20trajectory%20design" title="UAV trajectory design">UAV trajectory design</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20allocation" title=" power allocation"> power allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20efficient" title=" energy efficient"> energy efficient</a>, <a href="https://publications.waset.org/abstracts/search?q=downlink%20throughput" title=" downlink throughput"> downlink throughput</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20reinforcement%20learning" title=" deep reinforcement learning"> deep reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=DDPG" title=" DDPG"> DDPG</a> </p> <a href="https://publications.waset.org/abstracts/131461/trajectory-design-and-power-allocation-for-energy-efficient-uav-communication-based-on-deep-reinforcement-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131461.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25838</span> An Improved VM Allocation Algorithm by Utilizing Combined Resource Allocation Mechanism and Released Resources in Cloud Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md%20Habibul%20Ansary">Md Habibul Ansary</a>, <a href="https://publications.waset.org/abstracts/search?q=Chandan%20Garai"> Chandan Garai</a>, <a href="https://publications.waset.org/abstracts/search?q=Ranjan%20Dasgupta"> Ranjan Dasgupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Utilization of resources is always a great challenge for any allocation problem, particularly when resource availability is dynamic in nature. In this work VM allocation mechanism has been augmented by providing resources in a combined manner. This approach has some inherent advantages in terms of reduction of wait state for the pending jobs of some users and better utilization of unused resources from the service providers’ point of view. Moreover the algorithm takes care of released resources from the finished jobs as soon as those become available. The proposed algorithm has been explained by suitable example to make the work complete. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bid%20ratio" title="Bid ratio">Bid ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20service" title=" cloud service"> cloud service</a>, <a href="https://publications.waset.org/abstracts/search?q=virtualization" title=" virtualization"> virtualization</a>, <a href="https://publications.waset.org/abstracts/search?q=VM%20allocation%20problem" title=" VM allocation problem"> VM allocation problem</a> </p> <a href="https://publications.waset.org/abstracts/34024/an-improved-vm-allocation-algorithm-by-utilizing-combined-resource-allocation-mechanism-and-released-resources-in-cloud-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34024.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">396</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25837</span> Task Scheduling and Resource Allocation in Cloud-based on AHP Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zahra%20Ahmadi">Zahra Ahmadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Fazlollah%20Adibnia"> Fazlollah Adibnia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Scheduling of tasks and the optimal allocation of resources in the cloud are based on the dynamic nature of tasks and the heterogeneity of resources. Applications that are based on the scientific workflow are among the most widely used applications in this field, which are characterized by high processing power and storage capacity. In order to increase their efficiency, it is necessary to plan the tasks properly and select the best virtual machine in the cloud. The goals of the system are effective factors in scheduling tasks and resource selection, which depend on various criteria such as time, cost, current workload and processing power. Multi-criteria decision-making methods are a good choice in this field. In this research, a new method of work planning and resource allocation in a heterogeneous environment based on the modified AHP algorithm is proposed. In this method, the scheduling of input tasks is based on two criteria of execution time and size. Resource allocation is also a combination of the AHP algorithm and the first-input method of the first client. Resource prioritization is done with the criteria of main memory size, processor speed and bandwidth. What is considered in this system to modify the AHP algorithm Linear Max-Min and Linear Max normalization methods are the best choice for the mentioned algorithm, which have a great impact on the ranking. The simulation results show a decrease in the average response time, return time and execution time of input tasks in the proposed method compared to similar methods (basic methods). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hierarchical%20analytical%20process" title="hierarchical analytical process">hierarchical analytical process</a>, <a href="https://publications.waset.org/abstracts/search?q=work%20prioritization" title=" work prioritization"> work prioritization</a>, <a href="https://publications.waset.org/abstracts/search?q=normalization" title=" normalization"> normalization</a>, <a href="https://publications.waset.org/abstracts/search?q=heterogeneous%20resource%20allocation" title=" heterogeneous resource allocation"> heterogeneous resource allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=scientific%20workflow" title=" scientific workflow"> scientific workflow</a> </p> <a href="https://publications.waset.org/abstracts/145792/task-scheduling-and-resource-allocation-in-cloud-based-on-ahp-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145792.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">145</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25836</span> Multi-Objective Optimization of Combined System Reliability and Redundancy Allocation Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vijaya%20K.%20Srivastava">Vijaya K. Srivastava</a>, <a href="https://publications.waset.org/abstracts/search?q=Davide%20Spinello"> Davide Spinello</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents established 3<strong><sup>n</sup></strong> enumeration procedure for mixed integer optimization problems for solving multi-objective reliability and redundancy allocation problem subject to design constraints. The formulated problem is to find the optimum level of unit reliability and the number of units for each subsystem. A number of illustrative examples are provided and compared to indicate the application of the superiority of the proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=integer%20programming" title="integer programming">integer programming</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed%20integer%20programming" title=" mixed integer programming"> mixed integer programming</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20optimization" title=" multi-objective optimization"> multi-objective optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Reliability%20Redundancy%20Allocation" title=" Reliability Redundancy Allocation"> Reliability Redundancy Allocation</a> </p> <a href="https://publications.waset.org/abstracts/107208/multi-objective-optimization-of-combined-system-reliability-and-redundancy-allocation-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/107208.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">172</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25835</span> Dynamic Bandwidth Allocation in Fiber-Wireless (FiWi) Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eman%20I.%20Raslan">Eman I. Raslan</a>, <a href="https://publications.waset.org/abstracts/search?q=Haitham%20S.%20Hamza"> Haitham S. Hamza</a>, <a href="https://publications.waset.org/abstracts/search?q=Reda%20A.%20El-Khoribi"> Reda A. El-Khoribi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fiber-Wireless (FiWi) networks are a promising candidate for future broadband access networks. These networks combine the optical network as the back end where different passive optical network (PON) technologies are realized and the wireless network as the front end where different wireless technologies are adopted, e.g. LTE, WiMAX, Wi-Fi, and Wireless Mesh Networks (WMNs). The convergence of both optical and wireless technologies requires designing architectures with robust efficient and effective bandwidth allocation schemes. Different bandwidth allocation algorithms have been proposed in FiWi networks aiming to enhance the different segments of FiWi networks including wireless and optical subnetworks. In this survey, we focus on the differentiating between the different bandwidth allocation algorithms according to their enhancement segment of FiWi networks. We classify these techniques into wireless, optical and Hybrid bandwidth allocation techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fiber-wireless%20%28FiWi%29" title="fiber-wireless (FiWi)">fiber-wireless (FiWi)</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20bandwidth%20allocation%20%28DBA%29" title=" dynamic bandwidth allocation (DBA)"> dynamic bandwidth allocation (DBA)</a>, <a href="https://publications.waset.org/abstracts/search?q=passive%20optical%20networks%20%28PON%29" title=" passive optical networks (PON)"> passive optical networks (PON)</a>, <a href="https://publications.waset.org/abstracts/search?q=media%20access%20control%20%28MAC%29" title=" media access control (MAC)"> media access control (MAC)</a> </p> <a href="https://publications.waset.org/abstracts/43649/dynamic-bandwidth-allocation-in-fiber-wireless-fiwi-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43649.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">531</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25834</span> Predicting Data Center Resource Usage Using Quantile Regression to Conserve Energy While Fulfilling the Service Level Agreement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20I.%20Alutabi">Ahmed I. Alutabi</a>, <a href="https://publications.waset.org/abstracts/search?q=Naghmeh%20Dezhabad"> Naghmeh Dezhabad</a>, <a href="https://publications.waset.org/abstracts/search?q=Sudhakar%20Ganti"> Sudhakar Ganti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title="machine learning">machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction" title=" prediction"> prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20center" title=" data center"> data center</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20allocation" title=" resource allocation"> resource allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=green%20computing" title=" green computing"> green computing</a> </p> <a href="https://publications.waset.org/abstracts/147282/predicting-data-center-resource-usage-using-quantile-regression-to-conserve-energy-while-fulfilling-the-service-level-agreement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147282.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">108</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25833</span> Virtual Routing Function Allocation Method for Minimizing Total Network Power Consumption</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kenichiro%20Hida">Kenichiro Hida</a>, <a href="https://publications.waset.org/abstracts/search?q=Shin-Ichi%20Kuribayashi"> Shin-Ichi Kuribayashi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In a conventional network, most network devices, such as routers, are dedicated devices that do not have much variation in capacity. In recent years, a new concept of network functions virtualisation (NFV) has come into use. The intention is to implement a variety of network functions with software on general-purpose servers and this allows the network operator to select their capacities and locations without any constraints. This paper focuses on the allocation of NFV-based routing functions which are one of critical network functions, and presents the virtual routing function allocation algorithm that minimizes the total power consumption. In addition, this study presents the useful allocation policy of virtual routing functions, based on an evaluation with a ladder-shaped network model. This policy takes the ratio of the power consumption of a routing function to that of a circuit and traffic distribution between areas into consideration. Furthermore, the present paper shows that there are cases where the use of NFV-based routing functions makes it possible to reduce the total power consumption dramatically, in comparison to a conventional network, in which it is not economically viable to distribute small-capacity routing functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=NFV" title="NFV">NFV</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20allocation" title=" resource allocation"> resource allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=virtual%20routing%20function" title=" virtual routing function"> virtual routing function</a>, <a href="https://publications.waset.org/abstracts/search?q=minimum%20power%20consumption" title=" minimum power consumption"> minimum power consumption</a> </p> <a href="https://publications.waset.org/abstracts/52508/virtual-routing-function-allocation-method-for-minimizing-total-network-power-consumption" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52508.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">341</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25832</span> Energy-Aware Scheduling in Real-Time Systems: An Analysis of Fair Share Scheduling and Priority-Driven Preemptive Scheduling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Su%20Xiaohan">Su Xiaohan</a>, <a href="https://publications.waset.org/abstracts/search?q=Jin%20Chicheng"> Jin Chicheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Liu%20Yijing"> Liu Yijing</a>, <a href="https://publications.waset.org/abstracts/search?q=Burra%20Venkata%20Durga%20Kumar"> Burra Venkata Durga Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Energy-aware scheduling in real-time systems aims to minimize energy consumption, but issues related to resource reservation and timing constraints remain challenges. This study focuses on analyzing two scheduling algorithms, Fair-Share Scheduling (FFS) and Priority-Driven Preemptive Scheduling (PDPS), for solving these issues and energy-aware scheduling in real-time systems. Based on research on both algorithms and the processes of solving two problems, it can be found that Fair-Share Scheduling ensures fair allocation of resources but needs to improve with an imbalanced system load, and Priority-Driven Preemptive Scheduling prioritizes tasks based on criticality to meet timing constraints through preemption but relies heavily on task prioritization and may not be energy efficient. Therefore, improvements to both algorithms with energy-aware features will be proposed. Future work should focus on developing hybrid scheduling techniques that minimize energy consumption through intelligent task prioritization, resource allocation, and meeting time constraints. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=energy-aware%20scheduling" title="energy-aware scheduling">energy-aware scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=fair-share%20scheduling" title=" fair-share scheduling"> fair-share scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=priority-driven%20preemptive%20scheduling" title=" priority-driven preemptive scheduling"> priority-driven preemptive scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=real-time%20systems" title=" real-time systems"> real-time systems</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20reservation" title=" resource reservation"> resource reservation</a>, <a href="https://publications.waset.org/abstracts/search?q=timing%20constraints" title=" timing constraints"> timing constraints</a> </p> <a href="https://publications.waset.org/abstracts/169550/energy-aware-scheduling-in-real-time-systems-an-analysis-of-fair-share-scheduling-and-priority-driven-preemptive-scheduling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169550.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">119</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25831</span> Design Criteria for an Internal Information Technology Cost Allocation to Support Business Information Technology Alignment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andrea%20Schnabl">Andrea Schnabl</a>, <a href="https://publications.waset.org/abstracts/search?q=Mario%20Bernhart"> Mario Bernhart</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The controlling instrument of an internal cost allocation (IT chargeback) is commonly used to make IT costs transparent and controllable. Information Technology (IT) became, especially for information industries, a central competitive factor. Consequently, the focus is not on minimizing IT costs but on the strategic aligned application of IT. Hence, an internal IT cost allocation should be designed to enhance the business-IT alignment (strategic alignment of IT) in order to support the effective application of IT from a company’s point of view. To identify design criteria for an internal cost allocation to support business alignment a case study analysis at a typical medium-sized firm in information industry is performed. Documents, Key Performance Indicators, and cost accounting data over a period of 10 years are analyzed and interviews are performed. The derived design criteria are evaluated by 6 heads of IT departments from 6 different companies, which have an internal IT cost allocation at use. By applying these design criteria an internal cost allocation serves not only for cost controlling but also as an instrument in strategic IT management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=accounting%20for%20IT%20services" title="accounting for IT services">accounting for IT services</a>, <a href="https://publications.waset.org/abstracts/search?q=Business%20IT%20Alignment" title=" Business IT Alignment"> Business IT Alignment</a>, <a href="https://publications.waset.org/abstracts/search?q=internal%20cost%20allocation" title=" internal cost allocation"> internal cost allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=IT%20controlling" title=" IT controlling"> IT controlling</a>, <a href="https://publications.waset.org/abstracts/search?q=IT%20governance" title=" IT governance"> IT governance</a>, <a href="https://publications.waset.org/abstracts/search?q=strategic%20IT%20management" title=" strategic IT management"> strategic IT management</a> </p> <a href="https://publications.waset.org/abstracts/93449/design-criteria-for-an-internal-information-technology-cost-allocation-to-support-business-information-technology-alignment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93449.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">155</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25830</span> A Fuzzy Multiobjective Model for Bed Allocation Optimized by Artificial Bee Colony Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jalal%20Abdulkareem%20Sultan">Jalal Abdulkareem Sultan</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulhakeem%20Luqman%20Hasan"> Abdulhakeem Luqman Hasan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the development of health care systems competition, hospitals face more and more pressures. Meanwhile, resource allocation has a vital effect on achieving competitive advantages in hospitals. Selecting the appropriate number of beds is one of the most important sections in hospital management. However, in real situation, bed allocation selection is a multiple objective problem about different items with vagueness and randomness of the data. It is very complex. Hence, research about bed allocation problem is relatively scarce under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we develop a fuzzy multiobjective bed allocation model for overcoming uncertainty and multiple departments. Fuzzy objectives and weights are simultaneously applied to help the managers to select the suitable beds about different departments. The proposed model is solved by using Artificial Bee Colony (ABC), which is a very effective algorithm. The paper describes an application of the model, dealing with a public hospital in Iraq. The results related that fuzzy multi-objective model was presented suitable framework for bed allocation and optimum use. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bed%20allocation%20problem" title="bed allocation problem">bed allocation problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20bee%20colony" title=" artificial bee colony"> artificial bee colony</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20optimization" title=" multi-objective optimization"> multi-objective optimization</a> </p> <a href="https://publications.waset.org/abstracts/45374/a-fuzzy-multiobjective-model-for-bed-allocation-optimized-by-artificial-bee-colony-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45374.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">324</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25829</span> Enhancement of Capacity in a MC-CDMA based Cognitive Radio Network Using Non-Cooperative Game Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kalyani%20Kulkarni">Kalyani Kulkarni</a>, <a href="https://publications.waset.org/abstracts/search?q=Bharat%20Chaudhari"> Bharat Chaudhari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper addresses the issue of resource allocation in the emerging cognitive technology. Focusing the quality of service (QoS) of primary users (PU), a novel method is proposed for the resource allocation of secondary users (SU). In this paper, we propose the unique utility function in the game theoretic model of Cognitive Radio which can be maximized to increase the capacity of the cognitive radio network (CRN) and to minimize the interference scenario. The utility function is formulated to cater the need of PUs by observing Signal to Noise ratio. The existence of Nash equilibrium is for the postulated game is established. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20networks" title="cognitive networks">cognitive networks</a>, <a href="https://publications.waset.org/abstracts/search?q=game%20theory" title=" game theory"> game theory</a>, <a href="https://publications.waset.org/abstracts/search?q=Nash%20equilibrium" title=" Nash equilibrium"> Nash equilibrium</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20allocation" title=" resource allocation"> resource allocation</a> </p> <a href="https://publications.waset.org/abstracts/35688/enhancement-of-capacity-in-a-mc-cdma-based-cognitive-radio-network-using-non-cooperative-game-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35688.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">480</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25828</span> Quality-Of-Service-Aware Green Bandwidth Allocation in Ethernet Passive Optical Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tzu-Yang%20Lin">Tzu-Yang Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Chuan-Ching%20Sue"> Chuan-Ching Sue </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sleep mechanisms are commonly used to ensure the energy efficiency of each optical network unit (ONU) that concerns a single class delay constraint in the Ethernet Passive Optical Network (EPON). How long the ONUs can sleep without violating the delay constraint has become a research problem. Particularly, we can derive an analytical model to determine the optimal sleep time of ONUs in every cycle without violating the maximum class delay constraint. The bandwidth allocation considering such optimal sleep time is called Green Bandwidth Allocation (GBA). Although the GBA mechanism guarantees that the different class delay constraints do not violate the maximum class delay constraint, packets with a more relaxed delay constraint will be treated as those with the most stringent delay constraint and may be sent early. This means that the ONU will waste energy in active mode to send packets in advance which did not need to be sent at the current time. Accordingly, we proposed a QoS-aware GBA using a novel intra-ONU scheduling to control the packets to be sent according to their respective delay constraints, thereby enhancing energy efficiency without deteriorating delay performance. If packets are not explicitly classified but with different packet delay constraints, we can modify the intra-ONU scheduling to classify packets according to their packet delay constraints rather than their classes. Moreover, we propose the switchable ONU architecture in which the ONU can switch the architecture according to the sleep time length, thus improving energy efficiency in the QoS-aware GBA. The simulation results show that the QoS-aware GBA ensures that packets in different classes or with different delay constraints do not violate their respective delay constraints and consume less power than the original GBA. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Passive%20Optical%20Networks" title="Passive Optical Networks">Passive Optical Networks</a>, <a href="https://publications.waset.org/abstracts/search?q=PONs" title=" PONs"> PONs</a>, <a href="https://publications.waset.org/abstracts/search?q=Optical%20Network%20Unit" title=" Optical Network Unit"> Optical Network Unit</a>, <a href="https://publications.waset.org/abstracts/search?q=ONU" title=" ONU"> ONU</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20efficiency" title=" energy efficiency"> energy efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=delay%20constraint" title=" delay constraint"> delay constraint</a> </p> <a href="https://publications.waset.org/abstracts/94624/quality-of-service-aware-green-bandwidth-allocation-in-ethernet-passive-optical-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94624.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">284</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25827</span> Mathematical Model and Algorithm for the Berth and Yard Resource Allocation at Seaports</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ming%20Liu">Ming Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhihui%20Sun"> Zhihui Sun</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoning%20Zhang"> Xiaoning Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper studies a deterministic container transportation problem, jointly optimizing the berth allocation, quay crane assignment and yard storage allocation at container ports. The problem is formulated as an integer program to coordinate the decisions. Because of the large scale, it is then transformed into a set partitioning formulation, and a framework of branchand- price algorithm is provided to solve it. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=branch-and-price" title="branch-and-price">branch-and-price</a>, <a href="https://publications.waset.org/abstracts/search?q=container%20terminal" title=" container terminal"> container terminal</a>, <a href="https://publications.waset.org/abstracts/search?q=joint%20scheduling" title=" joint scheduling"> joint scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=maritime%20logistics" title=" maritime logistics"> maritime logistics</a> </p> <a href="https://publications.waset.org/abstracts/69918/mathematical-model-and-algorithm-for-the-berth-and-yard-resource-allocation-at-seaports" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69918.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">293</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25826</span> Qualitative Study Method on Case Assignment Adopted by Singapore Medical Social Workers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Joleen%20L.%20H.%20Lee">Joleen L. H. Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20F.%20Yen"> K. F. Yen</a>, <a href="https://publications.waset.org/abstracts/search?q=Janette%20W.%20P.%20Ng"> Janette W. P. Ng</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Woon"> D. Woon</a>, <a href="https://publications.waset.org/abstracts/search?q=Mandy%20M.%20Y.%20Lau"> Mandy M. Y. Lau</a>, <a href="https://publications.waset.org/abstracts/search?q=Ivan%20M.%20H.%20Woo"> Ivan M. H. Woo</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20N.%20Goh"> S. N. Goh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Case assignment systems are created to meet a need for equity in work distribution and better match between medical social workers' (MSWs) competencies and patients' problems. However, there is no known study that has explored how MSWs in Singapore assign cases to achieve equity in work distribution. Focus group discussions were conducted with MSWs from public hospitals to understand their perception on equitable workload and case allocation. Three approaches to case allocation were found. First is the point system where points are allocated to cases based on a checklist of presenting issues identified most of the time by non-MSWs. Intensity of case is taken into consideration, but allocation of points is often subject to variation in appreciation of roles of MSWs by the source of referral. Second is the round robin system, where all MSWs are allocated cases based on a roster. This approach resulted in perceived equity due to element of luck, but it does not match case complexity with competencies of MSWs. Third approach is unit-based allocation, where MSWs are assigned to attend to cases from specific unit. This approach helps facilitate specialization among MSWs but may result in MSWs having difficulty providing transdisciplinary care due to narrow set of knowledge and skills. Trade-offs resulted across existing approaches for case allocation by MSWs. Conversations are needed among Singapore MSWs to decide on a case allocation system that comes with trade-offs that are acceptable for patients and other key stakeholders of the care delivery system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=case%20allocation" title="case allocation">case allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=equity" title=" equity"> equity</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20social%20worker" title=" medical social worker"> medical social worker</a>, <a href="https://publications.waset.org/abstracts/search?q=work%20distribution" title=" work distribution"> work distribution</a> </p> <a href="https://publications.waset.org/abstracts/122201/qualitative-study-method-on-case-assignment-adopted-by-singapore-medical-social-workers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/122201.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">125</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25825</span> A Self-Coexistence Strategy for Spectrum Allocation Using Selfish and Unselfish Game Models in Cognitive Radio Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Noel%20Jeygar%20Robert">Noel Jeygar Robert</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20K.Vidya"> V. K.Vidya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cognitive radio is a software-defined radio technology that allows cognitive users to operate on the vacant bands of spectrum allocated to licensed users. Cognitive radio plays a vital role in the efficient utilization of wireless radio spectrum available between cognitive users and licensed users without making any interference to licensed users. The spectrum allocation followed by spectrum sharing is done in a fashion where a cognitive user has to wait until spectrum holes are identified and allocated when the licensed user moves out of his own allocated spectrum. In this paper, we propose a self –coexistence strategy using bargaining and Cournot game model for achieving spectrum allocation in cognitive radio networks. The game-theoretic model analyses the behaviour of cognitive users in both cooperative and non-cooperative scenarios and provides an equilibrium level of spectrum allocation. Game-theoretic models such as bargaining game model and Cournot game model produce a balanced distribution of spectrum resources and energy consumption. Simulation results show that both game theories achieve better performance compared to other popular techniques <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20radio" title="cognitive radio">cognitive radio</a>, <a href="https://publications.waset.org/abstracts/search?q=game%20theory" title=" game theory"> game theory</a>, <a href="https://publications.waset.org/abstracts/search?q=bargaining%20game" title=" bargaining game"> bargaining game</a>, <a href="https://publications.waset.org/abstracts/search?q=Cournot%20game" title=" Cournot game"> Cournot game</a> </p> <a href="https://publications.waset.org/abstracts/112222/a-self-coexistence-strategy-for-spectrum-allocation-using-selfish-and-unselfish-game-models-in-cognitive-radio-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/112222.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">299</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25824</span> The Lexicographic Serial Rule</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thi%20Thao%20Nguyen">Thi Thao Nguyen</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20McLennan"> Andrew McLennan</a>, <a href="https://publications.waset.org/abstracts/search?q=Shino%20Takayama"> Shino Takayama</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We study the probabilistic allocation of finitely many indivisible objects to finitely many agents. Well known allocation rules for this problem include random priority, the market mechanism proposed by Hylland and Zeckhauser [1979], and the probabilistic serial rule of Bogomolnaia and Moulin [2001]. We propose a new allocation rule, which we call the lexico-graphic (serial) rule, that is tailored for situations in which each agent's primary concern is to maximize the probability of receiving her favourite object. Three axioms, lex efficiency, lex envy freeness and fairness, are proposed and fully characterize the lexicographic serial rule. We also discuss how our axioms and the lexicographic rule are related to other allocation rules, particularly the probabilistic serial rule. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Efficiency" title="Efficiency">Efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=Envy%20free" title=" Envy free"> Envy free</a>, <a href="https://publications.waset.org/abstracts/search?q=Lexicographic" title=" Lexicographic"> Lexicographic</a>, <a href="https://publications.waset.org/abstracts/search?q=Probabilistic%20Serial%20Rule" title=" Probabilistic Serial Rule"> Probabilistic Serial Rule</a> </p> <a href="https://publications.waset.org/abstracts/124573/the-lexicographic-serial-rule" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/124573.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">148</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=6">6</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=7">7</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=8">8</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=9">9</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=10">10</a></li> <li class="page-item disabled"><span class="page-link">...</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=861">861</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=862">862</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20allocation%20method&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>