Optimal Selection of the Cluster Head in Wireless Sensor Networks by Combining the Multiobjective Genetic Algorithm and the Gravitational Search Algorithm

Seyed Reza Nabavi,Vahid Ostovari Moghadam,Mohammad Yahyaei Feriz Hendi,Amirhossein Ghasemi,Gengxin Sun

doi:10.1155/2021/2292580

Abstract

With the development of various applications of wireless sensor networks, they have been widely used in different areas. These networks are established autonomously and easily in most environments without any infrastructure and collect information of environment phenomenon for proper performance and analysis of events and transmit them to the base stations. The wireless sensor networks are comprised of various sensor nodes that play the role of the sensor node and the relay node in relationship with each other. On the other hand, the lack of infrastructure in these networks constrains the sources such that the nodes are supplied by a battery of limited energy. Considering the establishment of the network in impassable areas, it is not possible to recharge or change the batteries. Thus, energy saving in these networks is an essential challenge. Considering that the energy consumption rate while sensing information and receiving information packets from another node is constant, the sensor nodes consume maximum energy while performing data transmission. Therefore, the routing methods try to reduce energy consumption based on organized approaches. One of the promising solutions for reducing energy consumption in wireless sensor networks is to cluster the nodes and select the cluster head based on the information transmission parameters such that the average energy consumption of the nodes is reduced and the network lifetime is increased. Thus, in this study, a novel optimization approach has been presented for clustering the wireless sensor networks using the multiobjective genetic algorithm and the gravitational search algorithm. The multiobjective genetic algorithm based on reducing the intracluster distances and reducing the energy consumption of the cluster nodes is used to select the cluster head, and the nearly optimal routing based on the gravitational search algorithm is used to transfer information between the cluster head nodes and the sink node. The implementation results show that considering the capabilities of the multiobjective genetic algorithm and the gravitational search algorithm, the proposed method has improved energy consumption, efficiency, data delivery rate, and information packet transmission rate compared to the previous methods.

Highlights

The wireless sensor networks (WSNs) are comprised of distributed microdevices with various measurement capabilities that monitor the environment and transmit information to the end users
The multiobjective genetic algorithm based on reducing the intracluster distances and reducing the energy consumption of the member nodes (MN) is used to select the CH and the nearly optimal routing based on the gravitational search algorithm is used to transfer information between the cluster head nodes and the sink node
Various measures have been presented in the literature to evaluate the WSNs, which are introduced considering the research objectives mentioned in the first section

Summary

Introduction

The wireless sensor networks (WSNs) are comprised of distributed microdevices with various measurement capabilities that monitor the environment and transmit information to the end users. To increase the network lifetime and reduce energy consumption of the sensor nodes of the network, clustering techniques have been presented to achieve an efficient relationship among the sensor nodes [3, 4]. The CH nodes collect data from all sensor nodes of the cluster and transmit it to the base station after data aggregation and removing the duplicate data. The CH has to organize the network, collect data, and transmit data from the sensor nodes to the sink and the base station and it consumes more energy compared to other nodes [5,6,7,8]

Objectives

Results

Conclusion