A New Method for Multi-Objective TDMA Scheduling in Wireless Sensor Networks Using Pareto-Based PSO and Fuzzy Comprehensive Judgement

In wireless sensor networks with many-to-one transmission mode, a multi-objective TDMA (Time Division Multiple Access) scheduling model is presented, which concerns about the packet delay and the energy consumed on node state transition. To realize the scheme, a mapping between the problem and evolutionary algorithm is reasonably set up. A multi-objective particle swarm optimization based on Pareto optimality (PAPSO) is then proposed to solve such multi-objective optimization problem and find a better tradeoff between time delay and energy consumption.