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<!DOCTYPE html> <html xmlns="http://www.w3.org/1999/xhtml"> <head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"> <title>IoT Resource Allocation and Optimization Using Improved Reptile Search Algorithm</title>  <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <meta http-equiv="X-UA-Compatible" content="ie=edge"> <meta name="title" content="IoT Resource Allocation and Optimization Using Improved Reptile Search Algorithm"> <meta name="description" content="The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet. The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively."/> <meta name="keywords" content="Crossover, Improved Reptile Search Algorithm, Internet of Things, Levy flight, Resource Allocation "/>  <meta name="dc.title" content="IoT Resource Allocation and Optimization Using Improved Reptile Search Algorithm"> <meta name="citation_authors" content="Prabhakar Narasappa Kota"> <meta name="citation_authors" content="Pravin Balaso Chopade"> <meta name="citation_authors" content="Bhagvat D. Jadhav"> <meta name="citation_authors" content="Pravin Marotrao Ghate"> <meta name="citation_authors" content="Shankar Dattatray Chavan"> <meta name="dc.type" content="Article"> <meta name="dc.source" content="International Journal of Computer Networks & Communications (IJCNC) Vol.15, No.4"> <meta name="dc.date" content="2023/07/30"> <meta name="dc.identifier" content="10.5121/ijcnc.2023.15403"> <meta name="dc.publisher" content="AIRCC Publishing Corporation"> <meta name="dc.rights" content="http://creativecommons.org/licenses/by/3.0/"> <meta name="dc.format" content="application/pdf"> <meta name="dc.language" content="en"> <meta name="dc.description" content="The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet.The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively."/> <meta name="dc.subject" content="Crossover"> <meta name="dc.subject" content="Improved Reptile Search Algorithm"> <meta name="dc.subject" content="Internet of Things"> <meta name="dc.subject" content="Levy flight"> <meta name="dc.subject" content="Resource Allocation">   <meta name="prism.publicationName" content="International Journal of Computer Networks & Communications (IJCNC) "> <meta name="prism.publicationDate" content="2023/07/30"> <meta name="prism.volume" content="15"> <meta name="prism.number" content="04"> <meta name="prism.section" content="Article"> <meta name="prism.startingPage" content="39">   <meta name="citation_journal_title" content="International Journal of Computer Networks & Communications (IJCNC)"> <meta name="citation_publisher" content="AIRCC Publishing Corporation"> <meta name="citation_authors" content="Prabhakar Narasappa Kota, Pravin Balaso Chopade, Bhagvat D. Jadhav, Pravin Marotrao Ghate and Shankar Dattatray Chavan"> <meta name="citation_title" content="IoT Resource Allocation and Optimization Using Improved Reptile Search Algorithm"> <meta name="citation_online_date" content="2023/07/30"> <meta name="citation_issue" content="15"> <meta name="citation_firstpage" content="39"> <meta name="citation_authors" content="Prabhakar Narasappa Kota"> <meta name="citation_authors" content="Pravin Balaso Chopade"> <meta name="citation_authors" content="Bhagvat D. Jadhav"> <meta name="citation_authors" content="Pravin Marotrao Ghate"> <meta name="citation_authors" content="Shankar Dattatray Chavan"> <meta name="citation_doi" content="10.5121/ijcnc.2023.15403"> <meta name="citation_abstract_html_url" content="https://aircconline.com/abstract/ijcnc/v15n4/15423cnc03.html"> <meta name="citation_pdf_url" content="https://aircconline.com/ijcnc/V15N4/15423cnc03.pdf">   <meta property="og:site_name" content="AIRCC" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://aircconline.com/abstract/ijcnc/v15n4/15423cnc03.html"> <meta property="og:title" content="IoT Resource Allocation and Optimization Using Improved Reptile Search Algorithm"> <meta property="og:description" content="The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet.The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively."/>   <meta name="twitter:card" content="Proceedings" /> <meta name="twitter:site" content="AIRCC" /> <meta name="twitter:title" content="IoT Resource Allocation and Optimization Using Improved Reptile Search Algorithm" /> <meta name="twitter:description" content="The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet.The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively."/> <meta name="twitter:image" content="https://airccse.org/img/aircc-logo1.jpg" />   <meta name="google-site-verification" content="t8rHIcM8EfjIqfQzQ0IdYIiA9JxDD0uUZAitBCzsOIw" /> <meta name="yandex-verification" content="e3d2d5a32c7241f4" />  <style type="text/css"> a{ color:white; text-decoration:none; } ul li a{ font-weight:bold; color:#000; list-style:none; text-decoration:none; size:10px;} .imagess { height:90px; text-align:left; margin:0px 5px 2px 8px; float:right; border:none; } #left p { font-family:CALIBRI; font-size:0.90pc; margin-left: 20px; } .right { margin-right: 20px; } #button{ float: left; font-size: 17px; margin-left: 10px; height: 28px; width: 100px; background-color: #1e86c6; } </style> <link rel="icon" type="image/ico" href="../fav.ico"/> <link rel="stylesheet" type="text/css" href="../current.css" /> </head> <body> <div id="wap"> <div id="page"> <div id="top"> <table width="100%" cellspacing="0" cellpadding="0" > <tr><td colspan="3" valign="top"><img src="../top1.gif" /></td></tr> </table> </div> <div id="menu"> <a href="http://airccse.org/journal/ijcnc.html">Home</a> <a href="http://airccse.org/journal/j2editorial.html">Editorial</a> <a href="http://airccse.org/journal/j2paper.html">Submission</a> <a href="http://airccse.org/journal/j2indexing.html">Indexing</a> <a href="http://airccse.org/journal/j2special.html">Special Issue</a> <a href="http://airccse.org/journal/j2contact.html">Contacts</a> <a href="http://airccse.org" target="_blank">AIRCC</a></div> <div id="content"> <div id="left"> <h2>Volume 15, Number 4</h2> <h4 style="text-align:center;height:auto"><a>IoT Resource Allocation and Optimization Using Improved Reptile Search Algorithm</a></h4> <h3>  Authors</h3> <p class="#left">Prabhakar Narasappa Kota<sup>1</sup>, Pravin Balaso Chopade<sup>1</sup>, Bhagvat D. Jadhav<sup>2</sup>, Pravin Marotrao Ghate<sup>2</sup> and Shankar Dattatray Chavan<sup>3</sup>, <sup>1</sup>MES鈥檚 College of Engineering, India, <sup>2</sup>JSPM's Rajarshi Shahu College of Engineering, India, <sup>3</sup>Dr. D. Y. Patil Institute <br>of Technology, India </p> <h3>  Abstract</h3> <p class="#left right" style="text-align:justify">The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet. The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively. </p> <h3>  Keywords</h3> <p class="#left right" style="text-align:justify">Crossover, Improved Reptile Search Algorithm, Internet of Things, Levy flight, Resource Allocation </p><br> <button type="button" id="button"><a target="blank" href="/ijcnc/V15N4/15423cnc03.pdf">Full Text</a></button>   <button type="button" id="button"><a href="http://airccse.org/journal/ijc2023.html">Volume 15</a></button> <br><br><br><br><br> </div> <div id="right"> <div class="menu_right"> <ul> <li><a href="http://airccse.org/journal/jcnc_arch.html">Archives</a></li> </ul> </div><br /> <p align="center"> </p> <p align="center"> </p> </div> <div class="clear"></div> <div id="footer"><table width="100%" ><tr><td height="25" colspan="2"><br /><p align="center">® All Rights Reserved - AIRCC</p></td></table> </div> </div> </div> </div> </body> </html>