Open AccessAn Energy-Efficient Mobile Sink based Clustering using Simulated Annealing for Traversing
Author(s) -
Shubhangi Jadon
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.37990
Subject(s) - traverse , cluster analysis , shortest path problem , computer science , wireless sensor network , sink (geography) , simulated annealing , computer network , cluster (spacecraft) , path (computing) , efficient energy use , distributed computing , data mining , algorithm , engineering , artificial intelligence , theoretical computer science , electrical engineering , geography , graph , cartography , geodesy
Over recent decades, both scientific and commercial societies have been seeing the progress of wireless sensor networks (WSNs). Clustering is the most common form of growing WSN lifetime. The optimal number of cluster heads (CHs) & structure of clusters are the main problems in clustering techniques. The paper focuses on an efficient CH preference mechanism that rotates CH between nodes amid a greater energy level than others. Original energy, residual energy as well as the optimum value of CHs is assumed to be used by the algo for the choice of the next category of IoT-capable network cluster heads including ecosystem control, smart cities, or devices. The updated version of K-medium algo k-means++. Meanwhile, Simulated Annealing is implemented as the shortest path tree for mobile nodes which is constructed to establish the connection between the nodes for finding the shortest and secure path for data transmission hence resulting in faster data sending and receiving process. Keywords: WSN, CH selection, Residual energy (RE), Network Lifetime, Energy-efficient (EE)