Treffer: CDCS: Cluster-Based Distributed Compressed Sensing to Facilitate QoS Routing in Cognitive Video Sensor Networks.

Title:
CDCS: Cluster-Based Distributed Compressed Sensing to Facilitate QoS Routing in Cognitive Video Sensor Networks.
Authors:
Shen H; College of Computer Science and Technology, Nanjing Tech University, Nanjing 211816, China.; National Engineering Research Center of Communications and Networking, Nanjing University of Posts and Telecommunications, Nanjing 210003, China., Li L; College of Computer Science and Technology, Nanjing Tech University, Nanjing 211816, China., Wang T; College of Computer Science and Technology, Nanjing Tech University, Nanjing 211816, China., Bai G; College of Computer Science and Technology, Nanjing Tech University, Nanjing 211816, China.
Source:
Entropy (Basel, Switzerland) [Entropy (Basel)] 2019 Mar 28; Vol. 21 (4). Date of Electronic Publication: 2019 Mar 28.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: MDPI Country of Publication: Switzerland NLM ID: 101243874 Publication Model: Electronic Cited Medium: Internet ISSN: 1099-4300 (Electronic) Linking ISSN: 10994300 NLM ISO Abbreviation: Entropy (Basel) Subsets: PubMed not MEDLINE
Imprint Name(s):
Original Publication: Basel, Switzerland : MDPI, 1999-
References:
Sensors (Basel). 2016 May 10;16(5):. (PMID: 27171099)
Entropy (Basel). 2019 Mar 28;21(4):. (PMID: 33267059)
Grant Information:
61502230 National Natural Science Foundation of China; 61501224 National Natural Science Foundation of China; 61073197 National Natural Science Foundation of China; BK20150960 Natural Science Foundation of Jiangsu Province; 2018YFC0808500 National Key R&D Program of China; 15KJB520015 Natural Science Foundation of the Jiangsu Higher Education Institutions of China; GCZX012 National Engineering Research Center Program of Communications and Networking; 201608009 Nanjing Municipal Science and Technology Plan Project
Contributed Indexing:
Keywords: cognitive video sensor networks; distributed compressed sensing; information theory; quality-of-service; spatial correlation
Entry Date(s):
Date Created: 20201203 Latest Revision: 20240329
Update Code:
20250114
PubMed Central ID:
PMC7514829
DOI:
10.3390/e21040345
PMID:
33267059
Database:
MEDLINE

Weitere Informationen

Compressed sensing based in-network compression methods which minimize data redundancy are critical to cognitive video sensor networks. However, most existing methods require a large number of sensors for each measurement, resulting in significant performance degradation in energy efficiency and quality-of-service satisfaction. In this paper, a cluster-based distributed compressed sensing scheme working together with a quality-of-service aware routing framework is proposed to deliver visual information in cognitive video sensor networks efficiently. First, the correlation among adjacent video sensors determines the member nodes that participate in a cluster. On this basis, a sequential compressed sensing approach is applied to determine whether enough measurements are obtained to limit the reconstruction error between decoded signals and original signals under a specified reconstruction threshold. The goal is to maximize the removal of unnecessary traffic without sacrificing video quality. Lastly, the compressed data is transmitted via a distributed spectrum-aware quality-of-service routing scheme, with an objective of minimizing energy consumption subject to delay and reliability constraints. Simulation results demonstrate that the proposed approach can achieve energy-efficient data delivery and reconstruction accuracy of visual information compared with existing quality-of-service routing schemes.