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D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things.

Metin Aktas1, Murat Kuscu2, Ergin Dinc3

  • 1Aselsan, Inc., 06370, Ankara, Turkey.

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|March 15, 2018
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This study introduces Decoding Delay-based Distributed Source Coding (D-DSC) for wireless sensor networks (WSNs). D-DSC enhances energy efficiency by leveraging spatial correlation for reliable event estimation in the Internet of Sensing Things.

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) generate vast amounts of data.
  • Spatial correlation among sensor nodes offers opportunities for power conservation.
  • Existing Distributed Source Coding (DSC) methods can be further optimized for energy efficiency.

Purpose of the Study:

  • To propose a novel energy-efficient source coding mechanism for WSNs.
  • To improve upon classical DSC by incorporating a decoding delay concept.
  • To enhance event estimation and communication reliability in large-scale sensor networks.

Main Methods:

  • Network partitioning into clusters with clusterheads and members.
  • Clusterheads transmit uncompressed samples (side information); members transmit compressed samples.
  • Sink performs joint decoding and dynamically adjusts compression rates based on observed sensor sample correlation.

Main Results:

  • The proposed Decoding Delay-based Distributed Source Coding (D-DSC) improves energy efficiency.
  • D-DSC achieves reliable event communication and accurate signal estimation.
  • The method is suitable for massive sensor deployments in the Internet of Sensing Things (IoST).

Conclusions:

  • D-DSC offers a viable solution for energy-efficient data processing in WSNs.
  • The decoding delay concept effectively utilizes spatial correlation for improved performance.
  • This approach supports the development of practical signal detection and estimation applications.