Maximizing the Lifetime of a Barrier of Wireless Sensors

Kumar, Santosh; Lai, Ten-Hwang; Posner, Martin A.; Sinha, Prasun

doi:10.1109/tmc.2010.78

Cited by 104 publications

(73 citation statements)

References 22 publications

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“…In this paper, we extend the results of Kumar et al [13] who proposed an optimal solution to achieving k-barrier coverage without energy harvesting. The solution also has applications in achieving coverage in non-disk sensing regions and heterogeneous sensing regions as it is based on a coverage graph.…”

Section: Related Worksupporting

confidence: 62%

“…For this application, barriers made of sensors are set up to detect intruders' crossing of the barriers. The k-barrier coverage problem is to set up k disjoint barriers in a wireless sensor network with an objective of achieving the longest operation time [12], [13]. The network lifetime for k-barrier coverage is the longest time of having k operational disjoint barriers.…”

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confidence: 99%

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Maximizing continuous barrier coverage in energy harvesting sensor networks

DeWitt

Patt

Shi

2014

2014 IEEE International Conference on Communications (ICC)

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The lifetime of wireless sensor networks (WSNs) has been studied extensively. Lifetime is application specific, and long lifetime is desirable in general. In barrier coverage, it is desirable to have a large number of barriers active as well. Energy harvesting is an active research area in WSNs. In this paper we study the barrier coverage problem in energy harvesting WSNs. We develop an algorithm that finds a repeating sleep/wakeup schedule that can provide the continuous operation of the maximum number of barriers in an energy harvesting WSN. I. INTRODUCTIONThe lifetime of wireless sensor networks (WSNs) has been studied extensively [4]. Long lifetime is desirable. For instance, it can make the deployment of a network along a difficult border much less cost-prohibitive as it would reduce the need for frequent maintenance. However, network lifetime is application specific and thus necessitates individual study for different applications.One WSN application is detection of intruders for infrastructure protection and border control. For this application, barriers made of sensors are set up to detect intruders' crossing of the barriers. The k-barrier coverage problem is to set up k disjoint barriers in a wireless sensor network with an objective of achieving the longest operation time [12], [13]. The network lifetime for k-barrier coverage is the longest time of having k operational disjoint barriers. The parameter k has a large impact on the quality of the barrier coverage: the larger the k, the more robust the barrier coverage.Harvesting energy in WSNs has become an active research area [2], [6], [8], [9], [14], [17], [16]. A recent survey on energy harvesting in sensor networks [17] observes that "energy harvesting techniques have the potential to address the trade off between performance parameters and lifetime of sensor nodes." It is obvious by looking at the harvesting and sensing costs [16] that a naive approach to barrier coverage will not work. In a network that gathers energy with vibrational sensors harvesting at most .1mW that also employs light sensors using 1.155mW , it is not hard to see that such a network cannot be powered indefinitely in a barrier coverage application. Energy harvesting rates are much lower than energy consuming rates in sensor nodes. With energy harvesting techniques, there is still research to be done on extending network lifetime and increasing coverage.

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Section: Related Worksupporting

confidence: 62%

mentioning

confidence: 99%

Maximizing continuous barrier coverage in energy harvesting sensor networks

DeWitt

Patt

Shi

2014

2014 IEEE International Conference on Communications (ICC)

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“…A number of barrier coverage problems with respect to power issue have been explored in recent years [21]- [23]. Sensor scheduling [24], [25] is a widely used method to prolong the lifetime of networks. It helps to extend the lifetime of networks by inactivating some sensors while satisfying the coverage requirement.…”

Section: Related Workmentioning

confidence: 99%

Problem Specific MOEA/D for Barrier Coverage with Wireless Sensors

Zhang

Lee

et al. 2016

IEEE Trans. Cybern.

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Abstract-Barrier coverage with wireless sensors aims at detecting intruders who attempt to cross a specific area, where wireless sensors are distributed remotely at random. This paper considers limited-power sensors with adjustable ranges deployed along a linear domain to form a barrier to detect intruding incidents. We introduce three objectives to minimize: 1) total power consumption while satisfying full coverage; 2) the number of active sensors to improve the reliability; and 3) the active sensor nodes' maximum sensing range to maintain fairness. We refer to the problem as the tradeoff barrier coverage (TBC) problem. With the aim of obtaining a better tradeoff among the three objectives, we present a multiobjective optimization framework based on multiobjective evolutionary algorithm (MOEA)/D, which is called problem specific MOEA/D (PS-MOEA/D). Specifically, we define a 2-tuple encoding scheme and introduce a cover-shrink algorithm to produce feasible and relatively optimal solutions. Subsequently, we incorporate problem-specific knowledge into local search, which allows search procedures for neighboring subproblems collaborate each other. By considering the problem characteristics, we analyze the complexity and incorporate a strategy of computational resource allocation into our algorithm. We validate our approach by comparing with four competitors through several most-used metrics. The experimental results demonstrate that PS-MOEA/D is effective and outperforms the four competitors in all the cases, which indicates that our approach is promising in dealing with TBC.Index Terms-Barrier coverage, evolutionary algorithms, multiobjective optimization, wireless sensor networks (WSNs).

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“…The barrier coverage problem has been widely studied in the literature for static WSNs [1], [2], [14], [15], just to mention some of the most representative works. In this section we 978-1-4244-9268-8/11/$26.00 ©2011 IEEE only consider previous works on barrier coverage with mobile sensors due to space limitations.…”

Section: Related Workmentioning

confidence: 99%

MobiBar: Barrier Coverage with Mobile Sensors

Silvestri

2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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Critical homeland security applications such as monitoring zones contaminated by chemical or biological attacks and monitoring the spread of forest fires, require the timely creation of barrier of sensors along the border to be monitored. The strict time requirements and the hazardous nature of these contexts impede manual sensor positioning. Mobile Wireless Sensor Networks have the potential to meet the desired coverage requirements, by exploiting the device locomotion capabilities. In this paper we propose MOBIBAR, a distributed and asynchronous algorithm for k-barrier coverage with mobile sensors. We formally prove that MOBIBAR terminates in a finite time and that the final deployment provides the maximum level of barrier coverage with the available sensors. We compare MOBIBAR to a recent virtual force-based approach by means of simulations, which show the superiority of our solution. Furthermore, we show the self-healing capability of MOBIBAR to quickly recover from sudden sensor faults

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Maximizing the Lifetime of a Barrier of Wireless Sensors

Cited by 104 publications

References 22 publications

Maximizing continuous barrier coverage in energy harvesting sensor networks

Maximizing continuous barrier coverage in energy harvesting sensor networks

Problem Specific MOEA/D for Barrier Coverage with Wireless Sensors

MobiBar: Barrier Coverage with Mobile Sensors

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