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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/118873


    Title: MMQT: Maximizing the Monitoring Quality for Targets Based on Probabilistic Sensing Model in Rechargeable Wireless Sensor Networks
    Authors: Liao, Wen-Hwa;Dande, Bhargavi;Chang, Chih-Yung;Roy, Diptendu Sinha
    Keywords: Sensors;Wireless sensor networks;Batteries;Surveillance;Schedules;Energy harvesting
    Date: 2020-04-21
    Issue Date: 2020-07-07 12:10:27 (UTC+8)
    Abstract: In wireless sensor networks (WSNs), target coverage is an important issue which aims at finding a set of sensors to monitor the targets for maximizing both the surveillance quality and network lifetime. However, most of them assumed that each sensor is battery powered and the Boolean Sensing Model (BSM) is applied. Sensors powered by battery have a limited lifetime while the BSM is difficult to reflect the physical features of sensing. This paper proposes target coverage mechanisms, called C-MMQT and D-MMQT, which consider the solar-powered sensors and allows the battery to be recharged for maintaining the perpetual lifetime of sensor networks. The proposed mechanisms apply the Probabilistic Sensing Model (PSM) and consider that different targets have different importance. Two challenges have been overcome in this paper. First, each sensor is well scheduled for switching between recharging and working states for maintaining its perpetual lifetime since its battery is solar powered. Second, the sensors that are able to monitor the common target are well scheduled for cooperative sensing to maximize the surveillance quality since PSM is applied. Two efficient sensor schedules are proposed to maximize the surveillance quality of the bottleneck target which has the lowest surveillance quality. Performance study shows that the proposed mechanisms outperform the existing mechanisms in terms of Quality of Monitoring, Average utility, Fairness and Efficiency index.
    Relation: IEEE Access 8, p.77073-77088
    DOI: 10.1109/ACCESS.2020.2989199
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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