Minimum-energy reprogramming with guaranteed quality-of-sensing in software-defined sensor networks
Minimum-energy reprogramming with guaranteed quality-of-sensing in software-defined sensor networks
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DOI：
10.1109/icc.2014.6883333
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发表时间：
2014-06
期刊：
影响因子：
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通讯作者：
Deze Zeng;Peng Li;Song Guo;T. Miyazaki
中科院分区：
文献类型：
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作者：
Deze Zeng;Peng Li;Song Guo;T. Miyazaki
经过十年对专用无线传感器网络（WSN）的广泛研究，信息和通信技术的最新发展使得软件定义的传感器网络（SDSN）的实现变得可行，它能够适应各种应用需求并充分挖掘无线传感器网络的资源。在 SDSN 中，无线传感器节点可以通过无线编程技术针对不同的传感任务进行动态重新编程。对于给定的传感任务，通常需要保证一定的传感质量，例如覆盖率。直观地说，程序中部署的传感器越多，相应任务的传感质量就越高。然而，这是以高重编程能耗为代价的。在本文中，我们研究了如何为传感任务设计一种具有保证传感质量的节能重编程策略。为此，将解决两个问题：1）应重新编程的传感器子集，即重新编程传感器选择和2）程序分发路由。它们被共同考虑并表述为整数线性规划（ILP）问题，并在此基础上提出了一种低计算复杂度的算法。我们的算法的高效率通过大量的模拟研究得到了验证。
After a decade of extensive research on application-specific wireless sensor networks (WSNs), the recent development of information and communication technologies make it practical to realize software-defined sensor networks (SDSNs), which are able to adapt to various application requirements and to fully explore the resources of WSNs. In SDSNs, wireless sensor nodes can be dynamically reprogrammed for different sensing tasks via the over-the-air-programming technique. For a given sensing task, it is usually required to guarantee certain quality-of-sensing, e.g., coverage ratio. Intuitively, the more sensors are deployed with a program, the higher quality-of-sensing of the corresponding task can be achieved. However, this is at the expense of high reprogramming energy consumption. In this paper, we investigate how to design an energy-efficient reprogramming strategy with guaranteed quality-of-sensing for a sensing task. To this end, two issues will be tackled: 1) the subset of sensors that shall be reprogrammed, i.e., reprogramming sensor selection and 2) the program distribution routing. They are jointly considered and formulated as an integer linear programming (ILP) problem, based on which an algorithm with low computation complexity is then proposed. The high efficiency of our algorithm is validated by extensive simulation studies.