Modified Mobility Aware MAC Algorithm to Improve the Lifetime of Dynamic Wireless Sensor Network

Abstract

Cluster head selection and data processing are two of the most significant approaches for extending the lifetime of a wireless network. The approach entails a clustering mechanism focused on the deployment of nodes and the sensor’s coverage area. Cluster head gathers data from cluster nodes and compiles it before sending it to the base station. The election of cluster head and cluster members on a regular basis is a big challenge in a mobility conscious network. This paper represents new approach for appropriate cluster head selection and its member based on probability distribution function. The one-hop connection distance to reach all of the covered sensor nodes determines the starting probability of each node. The mobility aware clustering routing algorithm (MACRON) is used to elect cluster head based on LEACH algorithm, coverage and one-hop connectivity distance in terms of packet distribution, HOP distance, throughput, obtained signal power, and other factors. Furthermore, by evaluating the ratio of the current probability value to the cumulative probability value of all sensors, the MACRON algorithm dynamically calculates the shortest distance and normalizes the predicted probability. The simulation results show that the MACRON method is more successful than MEMAC and MMAC in extending the lifetime of mobility aware wireless sensor networks.