An Energy Aware Clustering Scheme for 5G-enabled Edge Computing based IoMT Framework

TL;DR

This paper proposes an energy-efficient clustering scheme for 5G-enabled IoMT systems using a Chicken Swarm Optimization algorithm to enhance network lifespan and performance.

Contribution

It introduces a multi-objective clustering algorithm tailored for IoMT, optimizing energy use and network longevity with a novel fitness function.

Findings

Reduced energy consumption compared to existing schemes

Extended network lifetime in simulations

Improved throughput and lower delay

Abstract

In recent years, 5G network systems start to offer communication infrastructure for Internet of Things (IoT) applications, especially for health care service pro-viders. In smart health care systems, edge computing enabled Internet of Medical Things (IoMT) is an innovative technology to provide online health care monitor-ing facility to patients. Here, energy consumption, along with extending the lifespan of biosensor network, is a key concern. In this contribution, a Chicken Swarm Optimization algorithm, based on Energy Efficient Multi-objective clus-tering scheme is applied in the context of IoMT system. An effective fitness func-tion is designed for cluster head selection., using multiple objectives, such as re-sidual energy, queuing delay, communication cost, link quality and node centrali-ty. Simulated outcomes of the proposed scheme are compared with the existing schemes in terms of parameters such as cluster formation time, energy consump-tion, network lifetime, throughput and propagation delay.