Fortifying Barrier-Coverage of Wireless Sensor Network with Mobile Sensor Nodes

Xu, Biaofei; Kim, Dong-Hyun; Li, Deying; Lee, Joong-Lyul; Jiang, Huaipan; Tokuta, Alade O.

doi:10.1007/978-3-319-07782-6_34

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…3.2 Single variable first-order grey model, GM (1,1) This section introduces GM(1,1) which can be used to predict the time that the next intruder will arrive at a sensor node based on the history of intruders collected by the sensor node. Suppose we have an initial intruder arrival time sequence measured by the sensor node, ða; bÞ T ¼ ½X T X À1 ½X T Y; where ð4Þ …”

Section: Network Modelmentioning

confidence: 99%

Strengthening barrier-coverage of static sensor network with mobile sensor nodes

Zhu

Kim

et al. 2015

Wireless Netw

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A wireless sensor network (WSN) provides a barrier-coverage over an area of interest if no intruder can enter the area without being detected by the WSN. Recently, barrier-coverage model has received lots of attentions. In reality, sensor nodes are subject to fail to detect objects within its sensing range due to many reasons, and thus such a barrier of sensors may have temporal loopholes. In case of the WSN for border surveillance applications, it is reasonable to assume that the intruders are smart enough to identify such loopholes of the barrier to penetrate. Once a loophole is found, the other intruders have a good chance to use it continuously until the known path turns out to be insecure due to the increased security. In this paper, we investigate the potential of mobile sensor nodes such as unmanned aerial vehicles and human patrols to fortify the barrier-coverage quality of a WSN of cheap and static sensor nodes. For this purpose, we first use a single variable first-order grey model, GM(1,1), based on the intruder detection history from the sensor nodes to determine which parts of the barrier is more vulnerable. Then, we relocate the available mobile sensor nodes to the identified vulnerable parts of the barrier in a timely manner, and prove this relocation strategy is optimal. Throughout the simulations, we evaluate the effectiveness of our algorithm.

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Section: Network Modelmentioning

confidence: 99%

Strengthening barrier-coverage of static sensor network with mobile sensor nodes

Zhu

Kim

et al. 2015

Wireless Netw

Self Cite

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“…Barrier coverage is thus a special case of partial-coverage. Due to the many important applications of barrier-coverage, in particular, intrusion detection, this type of sensor coverage has been studied extensively [10]- [17]. Figure 1(a) highlights a subset of sensors that provide barrier coverage to the area.…”

Section: Introductionmentioning

confidence: 99%

Improving the Lifetime of Non-penetrable Barrier Coverage in Sensor Networks

Cobb

2015

2015 IEEE 35th International Conference on Distributed Computing Systems Workshops

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An area covered by a wireless sensor network is protected, or covered, by a sensor barrier if there exists a subset of sensors that divide the area into two regions, such that no intruder can move from one region into the other without being detected. To maximize the length of time the area is covered by a barrier, the sensors can be divided into multiple disjoint subsets, where each subset is a barrier. By having only one barrier active at any time, the duration of the coverage is maximized. Algorithms exist that divide the sensors into the maximum number of barriers, and thus, maximize network lifetime. Recently, a new security problem was discovered, known as a barrier-breach, that allows an intruder to cross the area while one barrier is being replaced by another. This is dependent not on the structure of an individual sensor barrier, but in the relative shape of two consecutive sensor barriers. Heuristics have been presented to choose the maximum number of sensor barriers without a barrier breach. In this paper, we redefine the barrier breach problem in such a way that it motivates a different heuristic for its solution. Through simulations, we show that our heuristic significantly outperforms the best known heuristic, and thus, it improves network lifetime and/or fault-tolerance.

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“…In [Kim et al (2017)], Kim tried to maximize the lifetime of the barriers by scheduling mobile sensors to move around among partial barriers composed of static sensors. Xu [Xu et al (2014)] investigated the problem of allocating mobile sensors to fortify weak points in a barrier, where intruders may have a higher probability of visiting. The objective was to provide a minimum level of coverage, instead of minimizing the cost.…”

Section: Hybrid Sensor Deployment Problemmentioning

confidence: 99%

A study of sensor movement and selection strategies for strong barrier coverage

Zhang

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Fortifying Barrier-Coverage of Wireless Sensor Network with Mobile Sensor Nodes

Cited by 7 publications

References 11 publications

Strengthening barrier-coverage of static sensor network with mobile sensor nodes

Strengthening barrier-coverage of static sensor network with mobile sensor nodes

Improving the Lifetime of Non-penetrable Barrier Coverage in Sensor Networks

A study of sensor movement and selection strategies for strong barrier coverage

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