Approximation Algorithms for Barrier Sweep Coverage

Gorain, Barun; Mandal, Partha Sarathi

doi:10.1142/s0129054119500138

Cited by 14 publications

(6 citation statements)

References 28 publications

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“…As this becomes more difficult when the problem size gets larger, the authors of [37] suggested an immune-based algorithm. The authors of [38] suggested a barrier sweep coverage problem for covering not a whole area but finite critical curves with sector type sensors. They proved the barrier sweep coverage problem is an NP-hard problem and proposed an approximate algorithm.…”

Section: Sensor Deploymentmentioning

confidence: 99%

Algorithms for Finding Vulnerabilities and Deploying Additional Sensors in a Region with Obstacles

Kim

Lee

2021

Electronics

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Consider a two-dimensional rectangular region guarded by a set of sensors, which may be smart networked surveillance cameras or simpler sensor devices. In order to evaluate the level of security provided by these sensors, it is useful to find and evaluate the path with the lowest level of exposure to the sensors. Then, if desired, additional sensors can be placed at strategic locations to increase the level of security provided. General forms of these two problems are presented in this paper. Next, the minimum exposure path is found by first using the sensing limits of the sensors to compute an approximate “feasible area” of interest, and then using a grid within this feasible area to search for the minimum exposure path in a systematic manner. Two algorithms are presented for the minimum exposure path problem, and an additional subsequently executed algorithm is proposed for sensor deployment. The proposed algorithms are shown to require significantly lower computational complexity than previous methods, with the fastest proposed algorithm requiring O(n2.5) time, as compared to O(mn3) for a traditional grid-based search method, where n is the number of sensors, m is the number of obstacles, and certain assumptions are made on the parameter values.

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Section: Sensor Deploymentmentioning

confidence: 99%

Algorithms for Finding Vulnerabilities and Deploying Additional Sensors in a Region with Obstacles

Kim

Lee

2021

Electronics

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“…Gorain et al. took barrier sweep coverage into account [ 22 ]. They presented a energy restricted barrier sweep coverage problem and proposed

approximation algorithm.…”

Section: Related Workmentioning

confidence: 99%

Efficient Algorithms for Max-Weighted Point Sweep Coverage on Lines

Liang

Shen

2021

Sensors

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As an important application of wireless sensor networks (WSNs), deployment of mobile sensors to periodically monitor (sweep cover) a set of points of interest (PoIs) arises in various applications, such as environmental monitoring and data collection. For a set of PoIs in an Eulerian graph, the point sweep coverage problem of deploying the fewest sensors to periodically cover a set of PoIs is known to be Non-deterministic Polynomial Hard (NP-hard), even if all sensors have the same velocity. In this paper, we consider the problem of finding the set of PoIs on a line periodically covered by a given set of mobile sensors that has the maximum sum of weight. The problem is first proven NP-hard when sensors are with different velocities in this paper. Optimal and approximate solutions are also presented for sensors with the same and different velocities, respectively. For M sensors and N PoIs, the optimal algorithm for the case when sensors are with the same velocity runs in O(MN) time; our polynomial-time approximation algorithm for the case when sensors have a constant number of velocities achieves approximation ratio 12; for the general case of arbitrary velocities, 12α and 12(1−1/e) approximation algorithms are presented, respectively, where integer α≥2 is the tradeoff factor between time complexity and approximation ratio.

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“…In recent years, due to the development of charging technology, sensors with rechargeable battery have also begun to be widely used in various fields. There are currently two main charging methods, one is solar-powered [21], [22], [23], [24], and the other is mobile charging [24], [12], [9]. The paper [24] measures the pros and cons of the two charging methods, and proposes a hybrid framework to achieve the coverage quality and energy balance.…”

Section: Related Workmentioning

confidence: 99%

“…Due to the continuous movement of the mobile sensors in the sweep coverage network, mobile charging technology is more suitable to use to solve the challenge of limited energy. Gorain et al [12] first introduced a mobile sensor with charging capability into the sweep coverage problem, and proposed the energy-constrained fence sweep coverage problem. The mobile sensor needs to return to the base station for charging every charging period T , and realize the t-sweep coverage of the fence, t = T .…”

Section: Related Workmentioning

confidence: 99%

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Changeable Sweep Coverage Problem

Liang,

Shen

2021

Preprint

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Sweep coverage is to realize the periodic coverage of targets by planning the periodic sweeping paths of mobile sensors. It is difficult for sensors to reduce energy consumption by reducing the moving distances. Therefore, charging technology is the best way to extend the lifetime of the sweep coverage network. This paper studies the sweep coverage of rechargeable sensors: the sensors are rechargeable, constantly sweep between the target points and the charging stations not only tp meet the periodic coverage requirement of the target points, but also need to return to the charging stations during the charging period to avoid running out of energy. This paper proposes the general definition of Chargeable Sweep Coverage (CSC) problem for the first time, and studies the complexity of the CSC problem by analyzing CSC problems under different constraints, and then proposes two kinds of CSC problems under special constraints: 1) The sensors need to return to their original charging stations for charging; 2) The sensors can go to different charging stations for charging, and the number of charging stations is 2. Both of these problems are NP-hard. In this paper, these two problems are modeled as the maximum set coverage problem, and the approximation algorithms are obtained by reducing the number of candidate paths to polynomials. The validity and scalability of the proposed algorithms is proved by theoretical proof and experimental simulation.

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Approximation Algorithms for Barrier Sweep Coverage

Cited by 14 publications

References 28 publications

Algorithms for Finding Vulnerabilities and Deploying Additional Sensors in a Region with Obstacles

Algorithms for Finding Vulnerabilities and Deploying Additional Sensors in a Region with Obstacles

Efficient Algorithms for Max-Weighted Point Sweep Coverage on Lines

Changeable Sweep Coverage Problem

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