Task Allocation in Edge Computing Using Palmer’s Sequencing Algorithm

Abstract

AbstractMulti-access Edge Computing (MEC), formerly referred to as Mobile Edge Computing, is a network structure that authorizes and makes available of cloud computing facilities at the edge of the mobile network. Edge computing is a distributed system, which stores and manages the data at the edge in order to improve the quick responses to the mobile subscribers. The benefit of using edge computing is to reduce network congestion and reduce latency and to optimize the resources. MEC does major computations at the base locations by using edge servers. Computational offloading takes a lot of bandwidth and creates latency in the network. All the edge servers and resources must be utilized properly in order to avoid latency. Hence, load balancers are introduced to distribute the computations to the available resources and optimize them. So, as to optimize the network resources, a load balancing algorithm is used. Here, Palmer’s heuristics algorithm is proposed to optimize the network resources fairly. The proposed algorithm operates well at the edge load balancers to optimize the resources. The detailed study and working mechanism of the proposed algorithm is justified in this article.KeywordsMEC (mobile/multi-access edge computing)Virtual reality (VR)Flow shop sequencingLoad balancingAugmented reality (AR)MCC (Mobile cloud computing)Edge datacentres (EDC)CC (cloud computing)Virtual machine (VM) make-span and completion time