Energy efficient adaptive clustering hierarchy approach for wireless sensor networks

Hierarchical architecture, in combination with static structure, is a productive approach to Wireless Sensor Networks (WSNs) scalability as well as efficiency. Sensor nodes, a dual-layer framework, are extensively explored for several scenarios. This paper demonstrates the proposed novel clustering methodology representing it as the Minimum Weight Low Energy Adaptive Clustering Hierarchy (MW-LEACH). The Cluster Heads (CHs) are selected in MW-LEACH depending upon the surplus energy and the distances among them. With the proposed scheme, from the initial set, the nodes are chosen through surplus energy around the centre of the density, thus leading to the composition of the primary set of CH candidates. These candidates further accumulate data from their members by travelling in multiple directions forwarding that particular data to the BS. This specific methodology has lesser complications when it comes to message and time and is speedy and guarantees an appropriate fault tolerance level. In Matlab simulations and evaluations during the experimental phase, the proposed approach exceeds the advanced trendy protocols in reliance on performance metrics of throughput, packet delivery, energy intake, network lifespan (duration), and delays.