MH-CACA: multi-objective harmony search-based coverage aware clustering algorithm in WSNs

In this paper, multi-objective tournament harmony search-based coverage aware load balanced clustering algorithm (MH-CACA) is presented. The coverage aware memory consideration, random selection and tournament selection-based pitch adjustment to remove clumps and filling voids is imposed while harmony improvisation by altering the status of the on-duty sensors to off-duty and off-duty sensors to on-duty respectively. To show the effectiveness a large sample network is considered and the results are demonstrated for different parameters including coverage rate, dead gateways, dead sensors, energy consumption and network lifetime in comparison to the other existing techniques and found significantly improved in the proposed approach.