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Comparative performance analysis of various artificial immune networks applied to RFID reader-to-reader collision avoidance

机译:各种人工免疫网络在RFID读写器防撞中的比较性能分析

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Within a radio frequency identification (RFID) system, the reader-to-reader collision problem may occur when a group of readers operate simultaneously. The scheduling-based family, as one branch of RIFD reader collision avoidance methods, focuses on the allocation of time slots and frequency channels to RFID readers. Generally, the RFID reader-to-reader collision avoidance model can be translated as an optimization problem related with the communication resource allocation by maximizing the total effective interrogation area. Artificial immune networks are emerging heuristic evolutionary algorithms, which have been broadly applied to scientific computing and engineering applications. Since the first version of artificial immune networks for optimization occurred, a series of revised or derived artificial immune networks have been developed which aim at capturing more accurate solutions at higher convergence speed. For the RFID reader-to-reader collision avoidance model, this paper attempts to investigate the performance of six artificial immune networks in allocating communication resources to multiple readers. By following the spirits of artificial immune networks, the corresponding major immune operators are redesigned to satisfy the practice of RFID systems. By taking into account the effects of time slots and frequency channels, respectively, two groups of simulation experiments are arranged to examine the effectiveness of different artificial immune networks in optimizing the total effective interrogation area. Besides, a group of examination is executed to investigate the performance of six algorithms in solving different dimensionality of solution space in reader collision avoidance model. Meanwhile, a single group of simulation experiments are arranged to examine the computational efficiency of six artificial immune networks. The results demonstrate that six artificial immune networks perform well in searching the maximum total effective interrogation and are suitable to solve the RFID reader-to-reader collision avoidance model. (C) 2015 Elsevier B.V. All rights reserved.
机译:在射频识别(RFID)系统中,当一组读取器同时运行时,可能会发生读取器与读取器之间的冲突问题。作为RIFD阅读器防撞方法的一个分支,基于调度的系列专注于将时隙和频道分配给RFID阅读器。通常,通过最大化总有效询问区域,RFID读取器到读取器的冲突避免模型可以转换为与通信资源分配相关的优化问题。人工免疫网络是新兴的启发式进化算法,已广泛应用于科学计算和工程应用。自从出现第一个用于优化的人工免疫网络版本以来,已经开发了一系列经过修订或衍生的人工免疫网络,旨在以更高的收敛速度捕获更准确的解决方案。对于RFID读写器碰撞避免模型,本文试图研究六个人工免疫网络在向多个读取器分配通信资源方面的性能。通过遵循人工免疫网络的精神,重新设计了相应的主要免疫操作程序,以满足RFID系统的实践。通过分别考虑时隙和频道的影响,安排了两组模拟实验,以检验不同人工免疫网络在优化总有效询问区域方面的有效性。此外,还进行了一组检查,以研究六种算法在解决阅读器冲突避免模型中解决解决方案空间维数方面的性能。同时,安排了一组模拟实验来检验六个人工免疫网络的计算效率。结果表明,六个人工免疫网络在搜索最大总有效询问中表现良好,适合解决RFID读写器碰撞避免模型。 (C)2015 Elsevier B.V.保留所有权利。

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