CMTN-SP: A Novel Coverage-Control Algorithm for Moving-Target Nodes Based on Sensing Probability Model in Sensor Networks.

Zeyu Sun, Xiaofei Xing, Ben Yan, Zhiguo Lv

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Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

0.9field-weighted citation impact, top 23% of its field

1 · What the graph read from it

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0 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

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5 · Who and what money

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4 authors at 3 institutions in 1 country.

Zeyu SunSchool of Computer Science and Information Engineering, Luoyang Institute of Science and Technology, Luoyang 471023, China. zysun@lit.edu.cn.ORCID 0000-0002-0470-4203

Xiaofei XingSchool of Computer Science and Educational Software, Guangzhou University, Guangzhou 510006, China. xingxf@gzhu.edu.cn.

Ben YanSchool of Computer Science and Information Engineering, Luoyang Institute of Science and Technology, Luoyang 471023, China. yanben@lit.edu.cn.

Zhiguo LvSchool of Computer Science and Information Engineering, Luoyang Institute of Science and Technology, Luoyang 471023, China. lzg2008@lit.edu.cn.

Xidian University · CNGuangzhou University · CNLuoyang Institute of Science and Technology · CN

Funding

Foundation of Henan Educational Committee 19A520006Guangzhou Science, Technology and Innovation Commission 201707010284National Natural Science Foundation of China U1604149Natural Science Foundation of Guangdong Province 2016A030313540

6 · The paper itself

Abstract

The non-consecutive coverage problem for the target nodes in Sensor Networks could lead to the coverage blind area and a large amount of redundant data, which causes the bottleneck phenomenon for the communication link. A novel Coverage Control Algorithm for Moving Target Nodes Based on Sensing Probability Model (CMTN-SP) is proposed in this work. Firstly, according to the probability theory, we derive the calculation method for the expectation of the coverage quality with multiple joint nodes, which aims to reduce the coverage blind area and improving network coverage rate. Secondly, we employ the dynamic transferring mechanism of the nodes to re-optimize the deployment of the nodes, which alleviates the rapid exhaustion of the proper network energy. Finally, it is verified via the results of the simulation that the network coverage quality could not only be improved by the proposed algorithm, but the proposed algorithm could also effectively curb the rapid exhaustion of the node energy.

Indexed as

coverage controlnetwork coverage ratenetwork lifetimesensing probability modelsensor network

Identifiers

PMID30634676

DOI10.3390/s19020257

PMCPMC6359576

OpenAlexW2910166447

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.