Design of Randomly Deployed Heterogeneous Wireless Sensor Networks by Algorithms Based on Swarm Intelligence

This paper reports the design of a randomly deployed heterogeneous wireless sensor network (HWSN) with two types of nodes: a powerful node and an ordinary node. Powerful nodes, such as Cluster Heads (CHs), communicate directly to the data sink of the network, and ordinary nodes sense the desired information and transmit the processed data to powerful nodes. The heterogeneity of HWSNs improves the networks lifetime and coverage. This paper focuses on the design of a random network among HWSNs. In the design of a random HWSN, this paper uses algorithms based on the binary-valued versions of swarm intelligence, such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO). The design is then considered to be an optimization problem of how many powerful and ordinary nodes will combine to minimize the network cost, while guaranteeing a desired coverage during a given period. Simulation results show the performance of each algorithm for solving the defined optimization problem.