Real time flood disaster monitoring based on energy efficient ensemble clustering mechanism in wireless sensor network

In this article, energy efficient ensemble clustering method (EECM) with black widow optimization (EECM‐BWO) algorithm is proposed for effective data transmission with the help of real time flood disaster monitoring wireless sensor network (WSN). Initially, unified scalable ensemble clustering algorithm based on ensemble generation and consensus function is proposed for selecting the optimal routing path among the node using BWO algorithm. Then, biologically inspired routing black widow spiders optimization algorithm is proposed to trade off the nodes energy level, self‐organization, and self‐configuration in the WSN. The simulation is performed using NS2 simulator for validating the performance of the proposed EECM‐BWO method. Here, in node, low delay achieves 24.07%, 72.58%, 51.36%, 81.75%, 77.74%, high packet delivery ratio achieves 70.83%, 53.93%, 90.23%, 43.58%, 24.58%, low packet drop attains 77.93%, 72.76%, 61.56%, 51.87%, 34.35%, low energy consumption attains 75.9%, 52.94%, 65.81%, 58%, 41.2% compared with existing energy‐efficient clustering approach consolidated game theory as well as dual‐cluster‐head mode for WSNs energy‐aware clustering by cuckoo optimization approach (EECM‐COA), energy‐aware clustering‐based routing using multi‐path reliable transmission with routing and control board (EECM‐RCB‐MRT), adaptive repair algorithm with temporally ordered routing algorithms for flood control strategy (EECM‐AR‐TORA‐FCS), passive multi‐hop clustering algorithm (EECM‐PMC), dynamic source routing protocol based on genetic algorithm‐bacterial foraging optimization (DSR‐GA‐BFO).