Optimization of Wireless Sensor Networks using Artificial Intelligence and Ant Colony Optimization to Increase Network Lifetime and to Minimize Energy of Network

Energy consumption, network lifetime and packet loss are the major concerns in wireless sensor network. So for minimizing the energy of network and increasing the network lifetime, the ant colony optimization algorithm is proposed. Firstly, all the stages of Wireless sensor network such as node placement, network coverage, clustering and data aggregation and routing are optimized by the Genetic algorithm. Secondly, the proposed algorithm focuses on two parameters i.e. energy consumption and network lifetime. In Ant swarm algorithm, EAAR (Energy-aware ant-based routing) and ANTHOCNET (Adaptive nature-inspired algorithm for routing in mobile ad-hoc networks) protocols are used to minimize the energy of overall network and to follow the shortest path to reach the destination. These protocols are also used to find the number of dead nodes due to which packet loss and network lifetime improves. Lastly, APTEEN protocol with threshold energy finds the number of dead nodes by draining threshold energy to 50% and with maximum energy cluster head is selected. Results of EAAR, ANTHOCNET, APTEEN and proposed protocol (APTEEN with threshold energy) are analyzed in which proposed algorithm shows better results than APTEEN protocol where energy consumption is reduced from 90% to 60%.