A genetic algorithm-based energy-aware multi-hop clustering scheme for heterogeneous wireless sensor networks.

ABSTRACT:

Background

The energy-constrained heterogeneous nodes are the most challenging wireless sensor networks (WSNs) for developing energy-aware clustering schemes. Although various clustering approaches are proven to minimise energy consumption and delay and extend the network lifetime by selecting optimum cluster heads (CHs), it is still a crucial challenge.

Methods

This article proposes a genetic algorithm-based energy-aware multi-hop clustering (GA-EMC) scheme for heterogeneous WSNs (HWSNs). In HWSNs, all the nodes have varying initial energy and typically have an energy consumption restriction. A genetic algorithm determines the optimal CHs and their positions in the network. The fitness of chromosomes is calculated in terms of distance, optimal CHs, and the node's residual e

SUBMITTER: Muthukkumar R 

PROVIDER: S-EPMC9455049 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature