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Energy-efficient congestion detection and avoidance in sensor networks

Authors:

Chieh-Yih Wan,

Shane B. Eisenman,

Andrew T. CampbellAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 7, Issue 4

Article No.: 32, Pages 1 - 31

https://doi.org/10.1145/1921621.1921626

Published: 04 February 2011 Publication History

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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 distribution and rate of packet sources in the network. 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 multisource regulation. We present the detailed design, implementation, and evaluation of CODA using simulation and experimentation. We define three important performance metrics (i.e., energy tax, fidelity penalty, and power) 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 and 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.

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Kumar ALobiyal D(2024)Traffic Classification using Soft Computing for Congestion Management in WSN2024 International Conference on Automation and Computation (AUTOCOM)10.1109/AUTOCOM60220.2024.10486088(464-469)Online publication date: 14-Mar-2024
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Umar AKhalid ZAli MAbazeed MAlqahtani AUllah RSafdar H(2023)A Review on Congestion Mitigation Techniques in Ultra-Dense Wireless Sensor Networks: State-of-the-Art Future Emerging Artificial Intelligence-Based SolutionsApplied Sciences10.3390/app13221238413:22(12384)Online publication date: 16-Nov-2023
https://doi.org/10.3390/app132212384
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Energy-efficient congestion detection and avoidance in sensor networks

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Reviews

Reviewer: Debraj De

In wireless sensor networks, reliable, fair, and energy-efficient data collection at the base station has been a widely explored problem. Still, unsolved issues of organized congestion detection and avoidance exist in designing such data collection protocols. Problems occur, especially during bursts of events when a large set of event-triggered sensor nodes tries to simultaneously send data streams to the base station. The data traffic and the feedback acknowledgement traffic vie for access to the medium, radically reducing data throughput. In an effort to solve the problem, this paper proposes the congestion detection and avoidance (CODA) scheme. It includes three main mechanisms: receiver-based congestion detection, open-loop hop-by-hop backpressure, and closed-loop multisource regulation. The receiver-based congestion detection mechanism utilizes monitoring of buffer queue length and sampling-activated channel load monitoring. With open-loop hop-by-hop backpressure, the receiver node, on detecting congestion, sends a backpressure signal upstream toward the data sources. The closed-loop multisource regulation approach dynamically regulates all of the data sources with aggregated acknowledgment (ACK) control. The authors propose a hybrid window-based and rate-based scheme for the closed-loop control. Simulation experiments in ns-2 indicate that CODA improves the performance of data collection applications by mitigating congestion nodes and reducing the energy expense and fidelity penalty. The main contribution of this paper is the presentation of open- and closed-loop control after detecting congestion. Individually, the control methods are valid and effective; however, together, they are not particularly structured for a distributed system design. The congestion control and avoidance mechanism can execute simultaneously, but the interplay among them and its final effect on congestion is not clear. The proposed model and solution, however, will effectively help readers with a view of all of the local and distributed effects of congestion in data collection sensor networks. This work (an extension of the authors' 2003 work [1]) and its references are a bit dated. Still, it is worth reading for assessing the unsolved congestion problems in event-driven data collection sensor networks. One point to clarify for readers: the paper frequently uses the term "data dissemination" as the application scenario, even though the solution is for data collection at a base station. Online Computing Reviews Service

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cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 7, Issue 4

February 2011

252 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/1921621

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 04 February 2011

Accepted: 01 July 2010

Revised: 01 July 2010

Received: 01 January 2009

Published in TOSN Volume 7, Issue 4

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https://doi.org/10.1109/AUTOCOM60220.2024.10486088
Kumar ALobiyal D(2024)Congestion Management Techniques in WSNs: A Comparative StudyCryptology and Network Security with Machine Learning10.1007/978-981-97-0641-9_18(263-276)Online publication date: 23-Apr-2024
https://doi.org/10.1007/978-981-97-0641-9_18
Umar AKhalid ZAli MAbazeed MAlqahtani AUllah RSafdar H(2023)A Review on Congestion Mitigation Techniques in Ultra-Dense Wireless Sensor Networks: State-of-the-Art Future Emerging Artificial Intelligence-Based SolutionsApplied Sciences10.3390/app13221238413:22(12384)Online publication date: 16-Nov-2023
https://doi.org/10.3390/app132212384
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Djebaili YBilami A(2020)A Cross-Layer Fault Tolerant Protocol with Recovery Mechanism for Clustered Sensor NetworksSensor Technology10.4018/978-1-7998-2454-1.ch010(197-220)Online publication date: 2020
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Mahajan MKaur S(2020)Congestion Control Protocols in Wireless Sensor Networks: a comprehensive Survey2020 International Conference on Intelligent Engineering and Management (ICIEM)10.1109/ICIEM48762.2020.9160268(160-164)Online publication date: Jun-2020
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Efficient congestion avoidance mechanism

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