CODA: Congestion detection and avoidance in sensor networks

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CODA: Congestion detection and avoidance in sensor networks (2003)

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by Chieh-yih Wan , Shane B. Eisenman

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243 - 9 self

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@INPROCEEDINGS{Wan03coda:congestion,
    author = {Chieh-yih Wan and Shane B. Eisenman},
    title = {CODA: Congestion detection and avoidance in sensor networks},
    booktitle = {},
    year = {2003},
    pages = {266--279},
    publisher = {ACM Press}
}

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Abstract

Event-driven sensor networks operate under an idle or light load and then suddenly become active in response to a detected or monitored event. The transport of event impulses is likely to lead to varying degrees of congestion in the network depending on the sensing application. It is during these periods of event impulses that the likelihood of congestion is greatest and the information in transit of most importance to users. To address this challenge we propose an energy efficient congestion control scheme for sensor networks called CODA (COngestion Detection and Avoidance) that comprises three mechanisms: (i) receiver-based congestion detection; (ii) open-loop hop-by-hop backpressure; and (iii) closed-loop multi-source regulation. We present the detailed design, implementation, and evaluation of CODA using simulation and experimentation. We define two important performance metrics (i.e., energy tax and fidelity penalty) to evaluate the impact of CODA on the performance of sensing applications. We discuss the performance benefits and practical engineering challenges of implementing CODA in an experimental sensor network testbed based on Berkeley motes using CSMA. Simulation results indicate that CODA significantly improves the performance of data dissemination applications such as directed diffusion by mitigating hotspots, and reducing the energy tax with low fidelity penalty on sensing applications. We also demonstrate that CODA is capable of responding to a number of congestion scenarios that we believe will be prevalent as the deployment of these networks accelerates.

Keyphrases

sensor network congestion detection event impulse energy tax practical engineering challenge detailed design important performance metric event-driven sensor network sensing application performance benefit low fidelity penalty experimental sensor network energy efficient congestion control scheme network accelerates closed-loop multi-source regulation fidelity penalty congestion scenario open-loop hop-by-hop backpressure simulation result light load receiver-based congestion detection berkeley mote data dissemination application

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