Can I read A Genetic Algorithm Inspired Optimized Cluster Head Selection Method in Wireless Sensor Networks on EtoBox?

A Genetic Algorithm Inspired Optimized Cluster Head Selection Method in Wireless Sensor Networks by Biswa Mohan Sahoo; Hari Mohan Pandey; Tarachand Amgoth is a Computer Science article available to read on EtoBox.

What is A Genetic Algorithm Inspired Optimized Cluster Head Selection Method in Wireless Sensor Networks about?

In this paper, an optimized cluster head (CH) selection method based on genetic algorithm (NCOGA) is proposed which uses the adaptive crossover and binary tournament selection methods to prolong the lifetime of a heterogeneous wireless sensor network (WSN). The novelty of the proposed algorithms is the integration of multiple parameters for the CH selection in a heterogeneous WSN. NCOGA formulates fitness parameters by integrating multiple parameters like the residual energy, initial energy, distance to the sink, number of neighbors surrounded by a node, load balancing factor, and communicating mode decider (CMD). The parameters for load balancing and CMD are utilized to discover out the best candidate to be selected as a relay CH and for deciding the mode of communication (single or multi-hop) of CH. Further, these parameters are useful in avoiding hot-spot problem in the network. The working of the NCOGA starts based on the criteria "consider only those nodes which have energy higher than the pre-defined threshold energy". This criterion of nodes selection makes the NCOGA more efficient and quickly convergent. Extensive computer simulations are conducted to determine the effectiv

Who reads A Genetic Algorithm Inspired Optimized Cluster Head Selection Method in Wireless Sensor Networks?

Author

Biswa Mohan Sahoo; Hari Mohan Pandey; Tarachand Amgoth

Publisher

Elsevier BV

Published

2022

Language

EN

Field

Computer Science (Physical Sciences)