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

Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding...

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Vydané v:PloS one Ročník 13; číslo 3; s. e0193154
Hlavní autori: Aktas, Metin, Kuscu, Murat, Dinc, Ergin, Akan, Ozgur B.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States Public Library of Science 14.03.2018
Public Library of Science (PLoS)
Predmet:
Algorithms
Codes
Coding
Compression
Computer and Information Sciences
Correlation
Data compression
Decoding
Delay
Electrical engineering
Energy efficiency
Engineering and Technology
Engineering research
Evaluation
Information theory
Internet of Things
Management
Performance evaluation
Physical Sciences
Power consumption
Remote sensors
Research and Analysis Methods
Sensors
Signal detection
Signal processing
Wireless communications
Wireless networks
Wireless sensor networks
United Kingdom > UK
Istanbul Turkey
Turkey
ISSN:1932-6203, 1932-6203
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Popis
Shrnutí:Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples. Sink performs joint decoding of the compressed and uncompressed samples and then reconstructs the event signal using the decoded sensor readings. Based on the observed degree of the correlation among sensor samples, the sink dynamically updates and broadcasts the varying compression rates back to the sensor nodes. Simulation results for the performance evaluation reveal that D-DSC can achieve reliable and energy-efficient event communication and estimation for practical signal detection/estimation applications having massive number of sensors towards the realization of Internet of Sensing Things (IoST).
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Competing Interests: The addition of the funder, Aselsan Inc. (TR), does not alter our adherence to PLOS ONE policies on sharing data and materials.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0193154