Maximizing Coverage Efficiency in Wireless Networks using GWO: An Investigation of Hexagonal and Circular Tiling for Edge Server Placement

Edge servers (ESs) are crucial for enhancing performance and reliability in modern network systems. They minimize network latency, improve responsiveness, and optimize network utilization by bringing computational resources closer to end-users. This work explores the necessity of edge servers in modern network systems and their contribution to providing efficient and reliable quality of service (QoS). However, the conventional circle shape of edge server coverage is impractical due to its inherent drawbacks. The hexagonal range has emerged as a better alternative due to its balanced and uniform distribution of coverage areas. The Edge Server Placement Problem (ESPP) is NP-hard owing to multiple Base Stations (BS) and Edge Servers (ESs). Stochastic evolutionary metaheuristics are a natural choice. This study provides a comprehensive analysis of various approaches for edge server coverage, including the Grey Wolf Optimizer (GWO), Top-First approach, Random approach, and K-mean approach, among others. The open-source Shanghai Telecom dataset is used to evaluate the efficacy of these approaches with respect to QoS metrics such as work-load balance, energy consumption, and server utilisation rate. Our findings demonstrate that the GWO approach outperforms compared to other conventional approach K-mean by 8.60% in workload distribution, 5.19% in utilization rate and reduces energy consumption by 31.60%.