
		<paper>
			<loc>https://jjcit.org/paper/194</loc>
			<title>AGENT BASED APPROACH FOR TASK OFFLOADING IN EDGE COMPUTING</title>
			<doi>10.5455/jjcit.71-1673098290</doi>
			<authors>Hossein Morshedlou,Reza Vafa Shoar</authors>
			<keywords>Edge computing,Task offloading,Nash equilibrium,Agent,User satisfaction</keywords>
			<views>4670</views>
			<downloads>1157</downloads>
			<received_date>7-Jan.-2023</received_date>
			<revised_date>  24-Mar.-2023 and 9-Apr.-2023</revised_date>
			<accepted_date>  10-Apr.-2023</accepted_date>
			<abstract>Due to limited resource capacity in the edge network and a high volume of tasks offloaded to edge servers, edge 
resources may be unable to provide the required capacity for serving all tasks. As a result, some tasks should be 
moved  to  the  cloud,  which  may  cause  additional  delays.  This  may  lead  to  dissatisfaction  among  users  of  the 
transferred tasks. In this paper, a new agent-based approach to decision-making is presented about which tasks 
should  be  transferred  to  the  cloud  and  which  ones  should  be  served  locally.  This  approach  tries  to  pair  tasks 
with  resources, such  that  a  paired  resource  is  the  most  preferred  resource  by  the  user  or  task  among  all 
available  resources.  We  demonstrate  that  reaching  a  Nash  Equilibrium  point  can  satisfy  the  aforementioned 
condition.  A  game-theoretic  analysis  is  included  to  demonstrate that  the  presented  approach  increases  the 
average utility of the users and their level of satisfaction.</abstract>
		</paper>


