A discrete multi-swarm optimizer for radio frequency identification network scheduling

Due to the effectiveness, simple deployment and low cost, radio frequency identification （RFID） systems are used in a variety of applications to uniquely identify physical objects. The operation of RFID systems often involves a situation in which multiple readers physically located near one another may interfere with one another＇s operation. Such reader collision must be minimized to avoid the faulty or miss reads. Specifically, scheduling the colliding RFID readers to reduce the total system transaction time or response time is the challenging problem for large-scale RFID network deployment. Therefore, the aim of this work is to use a successful multi-swarm cooperative optimizer called pseo to minimize both the reader-to-reader interference and total system transaction time in RFID reader networks. The main idea of pS20 is to extend the single population PSO to the interacting multi-swarm model by constructing hierarchical interaction topology and enhanced dynamical update equations. As the RFID network scheduling model formulated in this work is a discrete problem, a binary version of PS20 algorithm is proposed. With seven discrete benchmark functions, PS20 is proved to have significantly better performance than the original PSO and a binary genetic algorithm, pS20 is then used for solving the real-world RFID network scheduling problem. Numerical results for four test cases with different scales, ranging from 30 to 200 readers, demonstrate the performance of the proposed methodology.

Random mating mayfly algorithm for RFID network planning

In order to improve robustness and efficiency of the radio frequency identification(RFID)network,a random mating mayfly algorithm(RMMA)was proposed.Firstly,RMMA introduced the mechanism of random mating into the mayfly algorithm(MA),which improved the population diversity and enhanced the exploration ability of the algorithm in the early stage,and find a better solution to the RFID nework planning(RNP)problem.Secondly,in RNP,tags are usually placed near the boundaries of the working space,so the minimum boundary mutation strategy was proposed to make sure the mayflies which beyond the boundary can keep the original search direction,as to enhance the ability of searching near the boundary.Lastly,in order to measure the performance of RMMA,the algorithm is then benchmarked on three well-known classic test functions,and the results are verified by a comparative study with particle swarm optimization(PSO),grey wolf optimization(GWO),and MA.The results show that the RMMA algorithm is able to provide very competitive results compared to these well-known meta-heuristics,RMMA is also applied to solve RNP problems.The performance evaluation shows that RMMA achieves higher coverage than the other three algorithms.When the number of readers is the same,RMMA can obtain lower interference and get a better load balance in each instance compared with other algorithms.RMMA can also solve RNP problem stably and efficiently when the number and position of tags change over time.

RFID network planning based on improved brain storm optimization algorithm

In order to improve the service quality of radio frequency identification(RFID) systems, multiple objectives should be comprehensively considered. An improved brain storm optimization algorithm GABSO, which incorporated adaptive learning operator and golden sine operator into the original brain storm optimization(BSO) algorithm, was proposed to solve the problem of RFID network planning(RNP). GABSO algorithm introduces learning operator and golden sine operator to achieve a balance between exploration and development. Based on GABSO algorithm, an optimization model is established to optimize the position of the reader. The GABSO algorithm was tested on the RFID model and dataset, and was compared with other methods. The GABSO algorithm’s tag coverage was increased by 9.62% over the Cuckoo search(CS) algorithm, and 7.70% over BSO. The results show that the GABSO algorithm could be successfully applied to solve the problem of RNP.

Delivering an Intelligent Foundation for RFID: Maximizing Network Efficiency with Cisco RFID Solutions

Radio frequency identification (RFID) is one of today s most anticipated technologies for a broad range of enterprises. Based on the promise of lower operating costs combined with more accurate product and asset information, organizations .Rfrom manufacturers to government agencies, retailers to healthcare providers , Rare introducing RFID technologies in the supply chain, for asset tracking and management, and for security and regulatory purposes.