Improved Cluster Based Data Gathering Using Ant Lion Optimization in Wireless Sensor Networks

Wireless sensor networks play a vital role in this digital world through various applications in several domains. The sensor networks are heavily energy constrained due to limited battery power. Therefore, the energy has to be optimally exploited to improve the lifetime and throughput of the network. Among the various existing approaches, cluster based routing algorithms are more popular for its balanced and less energy consumption throughout the communication network. Improper clustering often results in numerous individual nodes (sensor nodes which are not a part of any clusters). The individual nodes will send their information to the base station with high transmission power which heavily impacts the lifetime of the sensor network. Hence, a heuristic Ant Lion Optimization clustering algorithm for wireless sensor network is proposed in this paper. In the proposed work, the cluster head selection is modeled as a fitness function of the Antlion optimization algorithm, which improves the network performance. Also, a Discrete Ant Lion Optimization algorithm is applied to find the optimal data gathering tour for a mobile sink with minimal data collection tour length. The Discrete Ant Lion optimization algorithm computes the optimal order for the mobile sink to visit the selected cluster head nodes and collects their data. The simulation results show that the proposed clustering scheme improves the network lifetime, network throughput and it also reduces the number of individual nodes when compared to existing algorithms. Also, the proposed cluster-based mobile data gathering using the Ant Lion Optimization algorithm produces an optimal tour for the mobile sink to collect data from the cluster head node with minimum data collection tour distance.