Increasing Lifetime Using Whale Optimization Routing Algorithm in Wireless Sensor Networks

Authors

1 Faculty of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.

2 Faculty of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract

Following the development of wireless sensor networks, the need to design a low-waste, scalable, and long-life network is felt more than ever. Clustering and routing are widely used to minimize energy consumption and increase network lifetime, as important issues in wireless sensor networks. Since, in these networks, the largest amount of energy is spent on sending and receiving the data, the clustering technique done by collecting data on cluster heads has been found to influence the overall network performance; along with this, routine and efficient routing has also found to improve the network throughput. Therefore, multi-hop routing can increase the network lifetime and reduce the energy consumption by sensor nodes. In this paper, the main approach was using the mobile sinks attached to the public transportation vehicles, such as the bus to collect data in wireless sensor networks. The proposed protocol used multi-hop routing as well as Whale Optimization Algorithm to select cluster heads based on a fitness function, in which the amount of the remaining energy of the sensor nodes and the sum of the remaining energy of the adjacent sensor nodes were taken into account. Adopting this approach created a balance in the amount of energy consumption in sensor nodes. The proposed protocol was studied to validate the results obtained for the network lifetime and energy consumption. Independent and consecutive simulation results and statistical analysis indicates the superiority of the proposed protocol compared to other protocols. Also, the network lifetime improved by averagely 20% and the energy consumption reduced about 25% during the network activity.

Keywords


Volume 14, Issue 1
Winter and Spring 2021
Pages 33-51
  • Receive Date: 17 February 2020
  • Revise Date: 11 May 2021
  • Accept Date: 26 May 2021