Open AccessOptimal cluster head selection using modified rider assisted clustering for IoT
Author(s) -
Poluru Ravi Kumar,
Ramasamy Lokesh Kumar
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2020.0236
Subject(s) - cluster analysis , computer science , merge (version control) , cluster (spacecraft) , selection (genetic algorithm) , algorithm , sensor fusion , mathematical optimization , data mining , mathematics , artificial intelligence , computer network , information retrieval
The vital concern of this research work is to propose a new clustering algorithm based on IoT devices. This process is made up with four stages namely, Cluster Formation, Splitting and merging, CH selection and Data transformation. The first and foremost step is the cluster formation; in this k ‐mean clustering is exploited to cluster the network, where the count of needed clusters is optimally selected using a new algorithm. Further, this selection is to either split or merge the cluster structure. Subsequently, the proposed clustering model defines the optimal cluster head selection of each cluster by the proposed algorithm. Finally, in the data transmission phase, the delay optimized data fusion tree is subjected for reducing the manipulation of data fusion on transmission delay. More importantly, to solve all the optimization problems (optimal count of clusters and cluster heads), this paper introduces a new Cyclic Rider Optimization Algorithm (C‐ROA), which is the modification of Rider Optimization Algorithm (ROA). To the end, the performance of the adopted method is compared over the other classical models like FF, GWO, WOA and conventional ROA in terms of delay, normalized energy, alive nodes and cost function measures.