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Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System

机译:基于几何分布的人工免疫系统的排课优化算法

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摘要

In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.
机译:在射频识别(RFID)系统的多读取器环境(MRE)中,通常安排多个读取器通过在不同的时隙或频道上运行来查询随机化标签,以减少信号干扰。在此基础上,提出一种基于人工免疫系统的基于几何分布的多读者调度优化算法(GD-MRSOA-AIS),从资源分配的角度公平合理地调度读者操作。 GD-MRSOA-AIS由两部分组成,首先引入几何分布函数并结合公平性考虑,以生成用于阅读器操作的可行调度方案。此后,人工免疫系统(包括免疫克隆,免疫突变和免疫抑制)迅速将这些可行的免疫系统优化为最佳计划方案,以确保读者在更大的有效询问范围和更低的干扰下正常运行。与最新算法相比,仿真结果表明,GD-MRSOA-AIS可以有效地调度以更公平的资源分配方案运行的多个读取器,并在更大的有效询问范围内执行。

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