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Lightweight tracing for wireless sensor networks diagnostics.

机译:用于无线传感器网络诊断的轻量级跟踪。

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摘要

Wireless sensor networks (WSNs) are being increasingly deployed in various scientific as well as industrial domains to understand the micro-behavior of physical phenomena. WSNs are highly susceptible to post-deployment failures due to their in-situ deployments in harsh environments e.g., volcanoes. The traditional tools and techniques to handle such failures are inadequate because of inherent resource constraints of WSNs. The lack of diagnosis tools for post-deployment failures hinders the more widespread adoption of WSNs.;An execution trace containing events in their order of execution can play a crucial role in postmortem diagnosis of these failures. Obtaining such a trace, however, is challenging due to stringent resource constraints. In this dissertation, we propose an efficient distributed control-flow tracing technique for WSNs based on two key observations. First, WSN executions are highly repetitive, and second, WSNs exhibit restricted communication patterns. Our distributed control-flow tracing combines three novel lightweight techniques: (1) an efficient interprocedural control-flow encoding technique that generates a succinct control-flow trace of all events happening within a node, (2) a generic hybrid trace compression technique that significantly compresses traces, and (3) a space efficient message tracing technique that is amenable to compression. We show our tracing technique's effectiveness through failure case studies and efficiency through measurements and simulations.
机译:无线传感器网络(WSN)越来越多地部署在各种科学领域以及工业领域中,以了解物理现象的微观行为。由于WSN在恶劣的环境(例如火山)中原位部署,因此极易受到部署后故障的影响。由于WSN固有的资源限制,用于处理此类故障的传统工具和技术不足。缺乏用于部署后故障的诊断工具,阻碍了WSN的更广泛采用。包含按执行顺序的事件的执行跟踪可能在这些故障的事后诊断中发挥关键作用。然而,由于严格的资源限制,获得这样的踪迹是具有挑战性的。本文基于两个关键发现,提出了一种高效的无线传感器网络分布式控制流跟踪技术。首先,WSN的执行是高度重复的,其次,WSN表现出受限的通信模式。我们的分布式控制流跟踪结合了三种新颖的轻量级技术:(1)一种高效的过程间控制流编码技术,可生成节点内发生的所有事件的简洁控制流跟踪;(2)一种通用的混合跟踪压缩技术,可显着地减少压缩跟踪,以及(3)一种适用于压缩的节省空间的消息跟踪技术。我们通过故障案例研究来展示跟踪技术的有效性,并通过测量和模拟来展示效率。

著录项

  • 作者

    Sundaram, Vinaitheerthan.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Computer Science.;Engineering Computer.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 195 p.
  • 总页数 195
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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