An Improved Swarm Optimizer for RFID Network Scheduling

Abstract

Optimization of network scheduling is a significant way to improve the performance of the radio frequency identification (RFID) networks. This paper proposes an improved particle swarm optimization algorithm (PSO). It uses an animal foraging strategy to maintain a high diversity of swarms, which can protect them from premature convergence. The proposed algorithm is used to optimize the network performance by determining the optimal work status of readers. It has been tested in two different RFID network topologies to evaluate the effectivenesss. The simulation results reveal that the proposed algorithm outperforms the other algorithms in terms of optimization precision.