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Adaptive-compression based congestion control technique for wireless sensor networks.

Joa-Hyoung Lee1, In-Bum Jung

  • 1Department of Computer Science and Engineering, Kangwon National University, Chuncheon, Gangwondo, 200-701, Korea. jinnie4u@kangwon.ac.kr

Sensors (Basel, Switzerland)
|February 10, 2012
PubMed
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This study introduces an Adaptive Compression-based congestion control Technique (ACT) for wireless sensor networks. ACT effectively reduces data loss and transmission delays by adaptively compressing data packets during network congestion.

Area of Science:

  • Computer Science
  • Network Engineering
  • Data Compression

Background:

  • Wireless sensor networks (WSNs) face significant data loss and transmission delays due to network congestion.
  • Existing congestion control methods often struggle to maintain network efficiency and data integrity.

Purpose of the Study:

  • To propose a novel congestion control technique, Adaptive Compression-based congestion control Technique (ACT), for WSNs.
  • To enhance network efficiency and ensure fairness among sensor nodes during congestion.

Main Methods:

  • ACT employs a multi-stage compression approach: Discrete Wavelet Transform (DWT) for frequency domain transformation and priority assignment, Adaptive Differential Pulse Code Modulation (ADPCM) for data range reduction, and Run-Length Coding (RLC) for packet count minimization.
  • DWT classifies data into frequency groups, assigning priorities inversely proportional to frequency.
Keywords:
compressioncongestionqueue controlwireless sensor network

Related Experiment Videos

  • ADPCM's quantization step size is inversely proportional to data priorities, and RLC generates fewer packets for low-priority data.

    • Main Results:

    • Experimental results demonstrate that ACT significantly increases network efficiency compared to existing methods.
    • ACT ensures fairness among sensor nodes, preventing performance degradation for some nodes.
    • The technique achieves a high ratio of available data at the sink, minimizing data loss.

    Conclusions:

    • The proposed ACT provides an effective solution for congestion control in WSNs.
    • ACT's adaptive compression strategy enhances data transmission reliability and network performance.
    • The method offers a promising approach for managing congestion in resource-constrained wireless environments.