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首页> 外文期刊>Communications, IET >Compressed data-stream protocol: an energy-efficient compressed data-stream protocol for wireless sensor networks
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Compressed data-stream protocol: an energy-efficient compressed data-stream protocol for wireless sensor networks

机译:压缩数据流协议:用于无线传感器网络的节能压缩数据流协议

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摘要

In this study, the authors present an energy-efficient data compression protocol for data collection in wireless sensor networks (WSNs). WSNs are essentially constrained by motes' limited battery power and networks bandwidth. The authors focus on data compression algorithms and protocol development to effectively support data compression for data gathering in WSNs. Their design of compressed data-stream protocol (CDP) is generic in the sense that other lossless or lossy compression algorithms can be easily 'plugged' into the proposed protocol system without any changes to the rest of the CDP. This design intends to support various different WSN applications where users may prefer more specific compression algorithms, tailored to the sensing data characteristics in question, to their general algorithm. CDP is not only able to significantly reduce energy consumptions of data gathering in multi-hop WSNs, but also able to reduce sensor network traffic and thus avoid congestion accordingly. The proposed CDP is implemented on the tinyOS platform using the nesC programming language. To evaluate their work, the authors conduct simulations via TOSSIM and PowerTOSSIM-z with real-world sensor data. The results demonstrate the significance of CDP.
机译:在这项研究中,作者提出了一种节能数据压缩协议,用于无线传感器网络(WSN)中的数据收集。 WSN本质上受节点有限的电池电量和网络带宽的约束。作者专注于数据压缩算法和协议开发,以有效支持WSN中数据收集的数据压缩。他们的压缩数据流协议(CDP)设计是通用的,因为可以将其他无损或有损压缩算法轻松“插入”到建议的协议系统中,而无需对CDP的其余部分进行任何更改。该设计旨在支持各种不同的WSN应用程序,在这些应用程序中,用户可能更喜欢针对所讨论的传感数据特征量身定制的更具体的压缩算法,而不是其通用算法。 CDP不仅可以显着降低多跳WSN中收集数据的能耗,而且还可以减少传感器网络流量,从而避免拥塞。提议的CDP使用nesC编程语言在tinyOS平台上实现。为了评估他们的工作,作者通过TOSSIM和PowerTOSSIM-z使用真实的传感器数据进行了仿真。结果证明了CDP的重要性。

著录项

  • 来源
    《Communications, IET》 |2011年第18期|p.2673-2683|共11页
  • 作者

    Erratt N.; Liang Y.;

  • 作者单位

    Department of Computer and Information Science, Indiana University, Purdue University, Indianapolis, IN 46202, USA;

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  • 原文格式 PDF
  • 正文语种 eng
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