A hybrid Spatial Ant Lion optimization and utilitarian data transmission approach for intelligent optimization for energy-efficient wireless sensor networks.

Numerous researches on wireless sensor networks was conducted to design proficient algorithms not only to minimalize the exploitation of energy and delay, but also to increase the network lifetime and throughput. Optimization techniques will provide the proper balance among the parameters considered and help us to achieve the target of lifetime prolongation in wireless sensor networks. The proposed scheme comprises of two phases namely optimal cluster head selection and an effective data transmission phase. In phase 1, Spatial Ant Lion optimization will focus on optimal cluster head selection based on minimal computation on smaller population of nodes. The members inside the cluster are divided into two categories such as ant and the antlions. The ants are present in the innermost region of the cluster will gather and send the data to one of the antlions chosen as the cluster head. The fitness value is calculated only for the antlions based on energy retained in the node, distance between the sink to antlion and from the ants to antlion. Then the antlion with the highest fitness value will be selected as cluster head. After a waiting period the fitness value will be reevaluated to choose the new cluster head. In phase 2 utilitarian data transmission algorithm is proposed for effective data transmission. If the distance from the cluster head to the sink is lesser then the single hop data transmission will be employed otherwise two-hop data transmission employed for data transmission. The experimental evaluation was conducted considering parameters such as the length and width of the area, number of nodes, routing protocol, sink node placement, antlion population size, network topology, energy parameters (including free space energy, transmitter's energy, receiver's energy, and energy spent for data transfer), and the maximum number of iterations. Results demonstrate that the proposed model achieved a 1.86% increase in throughput, a 2.56% reduction in delay, and a 3.18% improvement in energy efficiency when compared to existing schemes such as PSO, ALO, and SA-AOA.