Particle Swarm Optimization based approach to solve the multiple sink placement problem in WSNs

A wireless sensor network (WSN) is a collection of tiny and limited-capability sensor nodes that report their sensed data to a data collector, referred to as a sink node. WSNs are used in many applications, but are challenged by memory and energy constraints. To address these issues, solutions have been proposed on different levels including the topological level where multiple sinks can be used in the network to reduce the number of hops between a sensor and its sink node. Topological level solutions are very crucial in time-sensitive applications where the maximum worst case delay incurred by a message to get from a sensor to the corresponding sink should be minimal or at least less than a certain value. In turn, the maximum worst case delay can be minimized by choosing near optimal locations of the sinks. Consequently the network lifetime will be extended since the energy consumed by the sensor nodes will be reduced. In this paper, we propose an efficient and robust approach based on Particle Swarm Optimization (PSO) heuristic to solve the multiple sink placement problem; more specifically we use Discrete PSO (DPSO) with local search (LS). We start by formulating the problem then discretizing it and finally applying PSO while introducing local search to the inner workings of the algorithm. When compared to Genetic Algorithm-based Sink Placement (GASP), which is considered the state-of-the-art in solving the multiple sink placement problem, our approach improved the results in most scenarios while requiring less runtime.