A novel energy-aware TDMA scheduling algorithm for wireless sensor networks

In wireless sensor networks, time division multiple access (TDMA) -based MAC can eliminate collisions, hence save energy and guarantee a bounded delay. However, the slot scheduling problem in TDMA is an NP problem. To minimized the total slots needed by a set of data collection tasks and saving the energy consumed on switching between the active and sleep states, a novel particle swarm optimization (PSO)-based scheduling algorithm called PSOSA is proposed in TDMA sensor networks. This algorithm can take full advantage of the searching ability of PSO, which is powerful for solving NP problems. Simulation results show that PSOSA requires less slots and energy to finish a set of data collection tasks. Moreover, compare with coloring algorithms, PSOSA have more flexibility to deal with a multi-objective optimization problem.