A Collective Intelligence-Based System to Improve Cluster Formation in Wireless Sensor Networks

Abstract

Wireless sensor networks (WSNs) are a new type of technology that aspires to provide new capabilities and solutions. Their use is continuing to increase in numerous areas. However, the scarce resources of the sensor nodes ought to be considered, mainly in terms of energy efficiency. As a result, one of the most pressing concerns in WSNs is the development of an energy-efficient routing system to extend network lifetime. One way to achieve energy efficiency would be using a clustering technique. In this work, we propose an approach based on computational intelligence to deal with the problem of sensor nodes clustering in a WSN. Thus, the ultimate goal of reducing energy costs is to extend the network lifetime. In this context, a data routing protocol within a WSN is developed using a computational technique. The performance analysis shows that our proposed protocol GA-LEACHPEGASIS (Genetic Algorithm LEACH PEGASIS) is able to optimize the network lifetime by minimizing energy consumption compared to the well-known LEACH protocol.