An Optimal Edge Server Placement Algorithm Based on Glowworm Swarm Optimization Technique

Presently, mobile edge computing has become an emerging and promising computing strategy to encompass a further dimension of ubiquitous computing. In this instance, edge servers are positioned near mobile devices to promote low latency and make the current network framework more proficient. The edge network receives computations as well as storage from the core network for faster and more reliable service. However, the location of the edge servers optimally presents the most significant challenge in the implementation of mobile edge computing architecture since finding an appropriate location for the servers is fundamental and critical. In order to evenly distribute workloads and decrease access delay across the edge server along with base stations, the edge server deployment dilemma is described as a constraint optimization issue in this work. To identify the most effective strategy, a modified Glowworm Swarm Optimization (GSO) technique has been proposed that reduces the overall quantity of edge server requirements. The proposed approach is simulated in MATLAB. The results demonstrate the behaviour of the proposed approach subject to varying densities of base stations with respect to clusters. The proposed algorithm is also found to perform better in contrast to the leading-edge Edge Server Placement algorithms.