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Top1. Introduction
Wireless Sensor Network (WSN) has become more attention for its potential applications in military and civil applications, healthcare, medical applications, agriculture, object tracking, security management, home automation, and energy management. The sensor networks comprise tiny and compact devices called motes or sensor nodes. The sensor nodes are deployed in remote or unattended locations. The sensor network collects the information from the environment, processes the information, and transmits the data to the end-users.
The sensor nodes are operated with a battery which plays an important role to estimate the lifetime of the network. The recharge or replacement of the battery is very difficult. So the amount of energy is consumed from the battery can be observed during the data processing and routing technology. Energy consumption is the most predominant factor for finding the lifetime of the network. Most of the energy is utilized for the data transmission process. The main goal is to perform the data processing and transmission along with improving the network lifetime by using energy management techniques.
Clustering is an important technique that organizes the sensor nodes hierarchically based on relative closeness to each other. The hierarchical approach is mainly utilized to form the clusters based on residual energy in the sensor nodes and the selection of the cluster head. LEACH is the best example of a hierarchical clustering-based routing protocol. Once the clusters are formed, the cluster head is assigned as the leader of the cluster members.
The responsibility of the cluster head is to perform the data aggregation and routing of the information from the cluster members to the base station. The cluster head is selected by considering the remaining energy of the cluster members. The cluster heads are having more burdens than the members in the clusters. Hence the cluster heads are rotated within the cluster members for sharing the work activities and also to improve the lifetime of the clusters.
The objectives of this paper can be summarized as follows:
- i)
Optimal clustering problem is formulated to prolong the network lifetime with the help of the number of alive nodes.
- ii)
Moth Flame Optimization algorithm is utilized to select the suitable optimal cluster head which considers the minimum distance among the sensor nodes and cluster head and residual energy of the sensor nodes.
- iii)
The proposed methodology is evaluated by using simulation studies. The simulation results achieve better results with the comparison of LEACH-C, BFA, and Dragonfly algorithm considering the performance metrics such as the number of alive nodes, network lifetime, and energy consumption.
The rest of the paper is organized as follows: Section 2 illustrates the related works for cluster head selection in wireless sensor networks. Section 3 elaborates the clustering in wireless sensor networks. Section 4 explains the biologically inspired algorithms and optimal cluster head selection in wireless sensor networks by using the Moth flame optimization algorithm. Section 5 shows the performance analysis of LEACH-C, BFA, and Dragonfly algorithms. Section 6 gives the conclusion and scope of the future work.