A novel non-disjoint partitioning algorithm for inter-cluster communication in wireless sensor networks

Abstract

Clustering accomplishes energy efficiency, seamless communication, and quality of service (QoS) metrics in wireless sensor networks. The idea of assimilating an overlapping method with clustering presents a virtuous inter-cluster communication in a distributed hostile environment. Therefore, a novel unequal non-disjoint partitioning algorithm called ratings based energy-efficient clustering overlap (REEC overlap) is proposed using K harmonic means (KHM) and fuzzy C means (FCM). The clusters are overlapped by combining the harmonic average distance, and FCM membership function. The cluster heads are chosen and rotated by rating value in which intersecting nodes are eliminated. The route is discovered using the energy required threshold with the least distance of nodes wherein frequency division multiple access (FDMA) is espoused as a data transmission medium. Simulation results show that the proposed work performs better than existing protocols. Moreover, REEC overlap is compared with REEC non-overlap to illustrate the energy dissipation of cluster heads that was proposed in the previous work.