WVSN Intrusion Detection Full-View Weak Barrier β-QoM Enhanced Construction Algorithm

Aiming at the problem of insufficient accuracy of the intruder image captured by wireless visual sensor network (WVSN), the intruder moving along a straight trajectory, a full-view weak barrier β-QoM enhancement algorithm CPFWBβEC for intrusion detection is proposed in this paper. The optimal full-v...

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Main Author: GUO Xinming, CAI Junwei
Format: Article
Language:zho
Published: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 2022-12-01
Series:Jisuanji kexue yu tansuo
Subjects:
Online Access:http://fcst.ceaj.org/fileup/1673-9418/PDF/2208006.pdf
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author GUO Xinming, CAI Junwei
author_facet GUO Xinming, CAI Junwei
author_sort GUO Xinming, CAI Junwei
collection DOAJ
description Aiming at the problem of insufficient accuracy of the intruder image captured by wireless visual sensor network (WVSN), the intruder moving along a straight trajectory, a full-view weak barrier β-QoM enhancement algorithm CPFWBβEC for intrusion detection is proposed in this paper. The optimal full-view weak barrier β-QoM enhancement construction in WVSN with nodes randomly and uniformly deployed is transformed into a set cover problem, and it is theoretically proven to be a NP-hard problem. Consequently, a heuristic algorithm CPFWBβEC is proposed. CPFWBβEC is mainly based on the greedy idea of sensor coverage area priority, so as to realize the β-QoM enhanced construction of intrusion detection full-view weak barrier in WVSN. The simulation results show that the average success rate of the barrier construction of the proposed algorithm is about 0.116 and 0.340 higher than that of W-GraProj and D-eTriB respectively. The average number of nodes to generate the barrier is reduced approximately by 35.5% and 56.1% compared with W-GraProj and D-eTriB respectively. In addition, with the increase of the value of β, the number of construction nodes of the weak barrier at full-view also rises up. At the same time, the time complexity of the algorithm CPFWBβEC is O(ncgn), which means it is suitable for environments with dense node deployment and high real-time requirement.
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spelling doaj.art-17884bbc01104055b393a710d90a4be72022-12-22T03:03:36ZzhoJournal of Computer Engineering and Applications Beijing Co., Ltd., Science PressJisuanji kexue yu tansuo1673-94182022-12-0116122765277410.3778/j.issn.1673-9418.2208006WVSN Intrusion Detection Full-View Weak Barrier β-QoM Enhanced Construction AlgorithmGUO Xinming, CAI Junwei01. School of Computer, Xianyang Normal University, Xianyang, Shaanxi 712000, China;2. School of Science, Ningbo University of Technology, Ningbo, Zhejiang 315211, ChinaAiming at the problem of insufficient accuracy of the intruder image captured by wireless visual sensor network (WVSN), the intruder moving along a straight trajectory, a full-view weak barrier β-QoM enhancement algorithm CPFWBβEC for intrusion detection is proposed in this paper. The optimal full-view weak barrier β-QoM enhancement construction in WVSN with nodes randomly and uniformly deployed is transformed into a set cover problem, and it is theoretically proven to be a NP-hard problem. Consequently, a heuristic algorithm CPFWBβEC is proposed. CPFWBβEC is mainly based on the greedy idea of sensor coverage area priority, so as to realize the β-QoM enhanced construction of intrusion detection full-view weak barrier in WVSN. The simulation results show that the average success rate of the barrier construction of the proposed algorithm is about 0.116 and 0.340 higher than that of W-GraProj and D-eTriB respectively. The average number of nodes to generate the barrier is reduced approximately by 35.5% and 56.1% compared with W-GraProj and D-eTriB respectively. In addition, with the increase of the value of β, the number of construction nodes of the weak barrier at full-view also rises up. At the same time, the time complexity of the algorithm CPFWBβEC is O(ncgn), which means it is suitable for environments with dense node deployment and high real-time requirement.http://fcst.ceaj.org/fileup/1673-9418/PDF/2208006.pdf|wireless visual sensor networks (wvsn)|full-view|weak barriers|β quality of monitoring (β-qom)
spellingShingle GUO Xinming, CAI Junwei
WVSN Intrusion Detection Full-View Weak Barrier β-QoM Enhanced Construction Algorithm
Jisuanji kexue yu tansuo
|wireless visual sensor networks (wvsn)|full-view|weak barriers|β quality of monitoring (β-qom)
title WVSN Intrusion Detection Full-View Weak Barrier β-QoM Enhanced Construction Algorithm
title_full WVSN Intrusion Detection Full-View Weak Barrier β-QoM Enhanced Construction Algorithm
title_fullStr WVSN Intrusion Detection Full-View Weak Barrier β-QoM Enhanced Construction Algorithm
title_full_unstemmed WVSN Intrusion Detection Full-View Weak Barrier β-QoM Enhanced Construction Algorithm
title_short WVSN Intrusion Detection Full-View Weak Barrier β-QoM Enhanced Construction Algorithm
title_sort wvsn intrusion detection full view weak barrier β qom enhanced construction algorithm
topic |wireless visual sensor networks (wvsn)|full-view|weak barriers|β quality of monitoring (β-qom)
url http://fcst.ceaj.org/fileup/1673-9418/PDF/2208006.pdf
work_keys_str_mv AT guoxinmingcaijunwei wvsnintrusiondetectionfullviewweakbarrierbqomenhancedconstructionalgorithm