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Using Fuzzy Logic for data priority aware collection in RFID sensing wireless networks

机译:使用模糊逻辑进行RFID传感无线网络中的数据优先级感知收集

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Long being used for identification purposes, a new set of applications is now available thanks to the development of RFID technology. One of which is remote sensing of environmental values using passive RFID tags. This leap forward allowed a more energy efficient and cheaper solution for applications like logistics or urban infrastructure monitoring. Nevertheless, serious issues raised with the use of RFID: (i) reading collisions and (ii) gathering of tag information. Indeed, tags information retrieved by readers have to be transmitted towards a base station through a multihop scheme which can interfere with neighboring readers activity. In this paper, we propose cross-layer solutions meant for both scheduling of readers' activity to avoid collisions, and a multihop routing towards base stations, to gather read tag data. This routing is performed with a data priority aware mechanism allowing end-to-end delay reduction of urgent data packets delivery up to 13% faster compared to standard ones. Using fuzzy logic, we combine several observed metrics to reduce the load of forwarding nodes and improve latency as well as data rate. We validate our proposal running simulations on industrial and urban scenarios.
机译:长期用于识别目的,由于RFID技术的开发,现在提供了一套新的应用程序。其中一个是使用被动RFID标签遥感环境值的遥感。这种飞跃允许物流或城市基础设施监测等应用更节能和更便宜的解决方案。然而,使用RFID的使用提出了严重的问题:(i)阅读碰撞和(ii)收集标签信息。实际上,读者检索的标签信息必须通过多跳方案向基站发送,该方法可以干扰相邻读取器活动。在本文中,我们提出了读者活动的跨层解决方案,以避免冲突,以及朝向基站的多跳路由,以收集读取标签数据。使用数据优先知识机制执行该路由,允许与标准值相比,迫切数据分组的端到端延迟减少高达13%。使用模糊逻辑,我们组合了几种观察指标以减少转发节点的负载并提高延迟以及数据速率。我们验证了我们对工业和城市情景的建议模拟。

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