An Analysis of Clustering Algorithms for Wireless Sensor Network Applications

Nowadays, wireless sensor networks (WSNs) have gained tremendous research interest in recent years across numerous domains such as military operations, security and surveillance systems, airplane routes, intelligent transport systems, environmental monitoring, animal tracking, health care, precision agriculture, and so on. The WSN comprises various sensor nodes that capture data in the form of signals and analyze the captured data to monitor the external environment and applications. The battery power and energy level of the sensor nodes are one of the major components of constructing any WSN. The network load and communication between the sensors are another challenging task in a WSN. Clustering is one of the significant approaches that resolve the scalability, energy efficiency, flexibility, maximizing network lifetime, communication time, connectivity, network load, and prolonging network lifetime inside WSNs. This chapter describes the clustering-based WSN in terms of various functionality, applications, advantages, challenges, load balancing, validation aspects, and classifications regarding WSN and clustering natures. The analysis of this chapter enables to assess the capabilities of the clustering approach in designing and managing WSNs in different types of applications.