Multiobjective ant lion optimizer based network planning for Internet of Things on TV white space

Abstract

SummaryIn this article, we consider the planning problem of Internet of Things networks working on TV White Space (TVWS), that is, optimizing the number of gateways and their locations to cover the M2M devices using the available TVWS spectrum. We first formulate it into a nondeterministic polynomial optimization problem, and then present the multiobjective ant lion optimizer (MOALO) algorithm with low complexity to solve it. Simulation results show that the proposed MOALO solution can achieve better performance than the classical multiobjective particle swarm optimization (MOPSO) algorithm. Considering the typical case with M2M devices distributed Gaussianly with the variance 80, to achieve 99% coverage, the number of gateways selected by the proposed MOALO algorithm can be 14% less than that obtained from the MOPSO algorithm.