Energy Efficient Cluster Head Selection in Internet of Things Using Minimum Spanning Tree (EEMST)

Abstract

ABSTRACT Internet of things network lifetime and energy issues are some of the most important challenges in today’s smart world. Clustering would be an effective solution to this, as all nodes would be arranged into virtual clusters, while one node will serve as the cluster head. The right selection of the cluster head will reduce energy consumption dramatically. This concept is more crucial for the internet of things, which is being widely distributed in environments such as forests or the smart agriculture sector. In this paper, an Energy Efficient Minimum Spanning Tree algorithm (EEMST) is presented to select the optimal cluster head and data routing based on graph theory for a multihop Internet of Things. This algorithm calculates the Euclidean distance-based minimum spanning tree based on a weighted graph. As a result, we use a weighted minimum spanning tree to choose the optimal cluster head and accordingly determine the shortest path for data transmission between member nodes and the cluster head. The proposed EEMST algorithm provides the possibility of intracluster multihop routing and also the possibility of intercluster single-hop routing. The simulated experimental results approve a significant improvement of the proposed algorithm in the IoT systems’ lifetime compared to the baselines.