IGAA: An Efficient Optimization Technique for RFID Network Topology Design in Internet of Things

Most RFID applications in the Internet of Things (IoTs) use multiple readers to read the IDs of multiple tags and form the RFID network. In such a network, unguarded reader deployment may generate over-crowded readers, cause interferences and, as a result, increases the deployment cost while degrading tag detection. Seeing that desirable reader deployment is crucial for RFID system performance, this paper introduces an optimizationbased IGAA approach which outperforms existing RFID topology designs by turning up more favorable reader deployment and system performance. The new approach employs an advanced multi-objective fitness function and improved genetic annealing algorithms (GAA) to pursue a better RFID topology design. By involving an improved gene-stirring operation to help preserve good genes and locate optimal solutions for reader deployment, it is simple in operation but effective in practice. Experimental evaluation shows that when compared with related approaches, IGAA can yield better solution quality with less search time.