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Probabilistic Missing-tag Detection and Energy-Time Tradeoff in Large-scale RFID Systems

机译:大型RFID系统中的概率丢失标签检测和能量时间折衷

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RFID (radio frequency identification) technologies are poised to revolutionize retail, warehouse and supply chain management. One of their interesting applications is to automatically detect missing tags (and the associated objects) in a large storage space, In order to timely catch any missing event such as theft, the detection operation may have to be performed frequently. Because RFID systems typically work under low-rate channels, past research has focused on reducing execution time of a detection protocol, in order to prevent excessively-long protocol execution from interfering normal inventory operations. However, when active tags are used to provide a large spatial coverage, energy efficiency becomes critical in prolonging the lifetime of these battery-powered tags. Existing literature lacks thorough study on how to conserve energy in the process of missing-tag detection and how to jointly optimize energy efficiency and time efficiency. This paper makes two important contributions: First, we propose a novel protocol design that takes both energy efficiency and time efficiency into consideration. It achieves multi-fold reduction in both energy cost and execution time when comparing with the best existing work. In some cases, the reduction is more than an order of magnitude. Second, we reveal a fundamental energy-time tradeoff in missing-tag detection. Through our analytical framework, we are able to flexibly control the tradeoff through a couple of system parameters in order to achieve desirable performance.
机译:RFID(射频识别)技术有望彻底改变零售,仓库和供应链管理。他们有趣的应用程序之一是自动检测大存储空间中的丢失标签(和关联的对象)。为了及时捕获任何丢失事件(例如盗窃),可能必须频繁执行检测操作。因为RFID系统通常在低速率信道下工作,所以过去的研究集中在减少检测协议的执行时间上,以防止过长的协议执行干扰正常的库存操作。但是,当使用有源标签提供较大的空间覆盖范围时,能源效率对于延长这些电池供电标签的使用寿命至关重要。现有文献缺乏关于丢失标签检测过程中如何节约能源以及如何共同优化能源效率和时间效率的深入研究。本文做出了两个重要的贡献:首先,我们提出了一种新颖的协议设计,该设计同时考虑了能源效率和时间效率。与最佳的现有工作相比,它可以在能源成本和执行时间方面实现多方面的降低。在某些情况下,减少幅度超过一个数量级。其次,我们揭示了丢失标签检测中的基本能量时间折衷。通过我们的分析框架,我们能够通过几个系统参数灵活地控制权衡,以实现理想的性能。

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