On Multi-round Sensor Deployment for Barrier Coverage

Eftekhari, Mohsen; Narayanan, Lata; Opatrný, Jaroslav

doi:10.1109/mass.2013.85

Cited by 13 publications

(10 citation statements)

References 11 publications

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“…The authors introduced and studied the notions of both strong and weak barrier coverage in this paper, and studied coverage of a narrow belt-like region. Since then the problem has been extensively studied, for example, see [2,3,13,18,20].…”

Section: Related Workmentioning

confidence: 99%

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Weak Coverage of a Rectangular Barrier

Dobrev

Kranakis

Kriz̧anc

et al. 2017

Lecture Notes in Computer Science

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Assume n wireless mobile sensors are initially dispersed in an ad hoc manner in a rectangular region. They are required to move to final locations so that they can detect any intruder crossing the region in a direction parallel to the sides of the rectangle, and thus provide weak barrier coverage of the region. We study three optimization problems related to the movement of sensors to achieve weak barrier coverage: minimizing the number of sensors moved (MinNum), minimizing the average distance moved by the sensors (MinSum), and minimizing the maximum distance moved by the sensors (MinMax). We give an O(n 3/2 ) time algorithm for the MinNum problem for sensors of diameter 1 that are initially placed at integer positions; in contrast we show that the problem is NP-hard even for sensors of diameter 2 that are initially placed at integer positions. We show that the MinSum problem is solvable in O(n log n) time for homogeneous range sensors in arbitrary initial positions for the Manhattan metric, while it is NP-hard for heterogeneous sensor ranges for both Euclidean and Manhattan metrics. Finally, we prove that even very restricted homogeneous versions of the MinMax problem are NP-hard.

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Section: Related Workmentioning

confidence: 99%

“…Barrier coverage was introduced in [17], and has been extensively studied since then [2,3,13,18,20,8,9]. The problem was posed as the deployment of sensors in a narrow belt-like rectangular region in such a way that any intruder crossing the belt would be detected.…”

Section: Introductionmentioning

confidence: 99%

Weak Coverage of a Rectangular Barrier

Dobrev

Kranakis

Kriz̧anc

et al. 2017

Lecture Notes in Computer Science

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“…An important setting in considerations for barrier coverage is when the sensors are placed at random on the barrier according to the uniform distribution. Clearly, when the sensor dispersal on the barrier is random then coverage depends on the sensor density and some authors have proposed using several rounds of random dispersal for complete barrier coverage [9,18]. Another approach is to have the sensors relocate from their initial position to a new position on the barrier so as to achieve complete coverage [5,6,8,16].…”

Section: Related Workmentioning

confidence: 99%

On the displacement for covering a d-dimensional cube with randomly placed sensors

Kapelko

Kranakis

2016

Ad Hoc Networks

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Consider n sensors placed randomly and independently with the uniform distribution in a d−dimensional unit cube (d ≥ 2). The sensors have identical sensing range equal to r, for some r > 0. We are interested in moving the sensors from their initial positions to new positions so as to ensure that the d−dimensional unit cube is completely covered, i.e., every point in the d−dimensional cube is within the range of a sensor. If the i-th sensor is displaced a distance d i , what is a displacement of minimum cost? As cost measure for the displacement of the team of sensors we consider the a-total movement defined as the sum, for some constant a > 0. We assume that r and n are chosen so as to allow full coverage of the d−dimensional unit cube and a > 0.The main contribution of the paper is to show the existence of a tradeoff between the d−dimensional cube, sensing radius and a-total movement. The main results can be summarized as follows for the case of the d−dimensional cube. If the d−dimensional cube sensing radius is

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“…Clearly, a sufficient density of random nodes is necessary to achieve property that the distance between two sensors is less than v (see [18]) and some authors have proposed using several rounds of random displacement for desired connectivity [11], [47]. Another approach is to have the sensors move from their initial location to a new position so as to achieve the desired connectivity property.…”

Section: Introductionmentioning

confidence: 99%

On the Energy in Displacement of Random Sensors for Connectivity and Interference

Kapelko

2020

Proceedings of the 21st International Conference on Distributed Computing and Networking

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This paper investigates the problem of the minimilization of energy consumption in reallocation of wireless mobile sensors network (WMSN) to assure good communication without interference.Fix d ∈ N \ {0}. Assume n sensors are initially randomly placed in the hyperoctant [0, ∞) d according to d identical and independent Poisson processes each with arrival rate λ > 0.Let 0 < s ≤ v be given real numbers. We are allowed to move the sensors, so that every two consecutive sensors are placed at distance greater than or equal to s and less than or equal to v.Fix a ≥ 1. Assume that i−th sensor is displaced a distance equal to m(i). The cost measure for the displacement of the team of sensors is the sum n i=1 d a i (a−total movement). In this work, we discover and explain a sharp decline and a sharp increase (a threshold phenomena) in the expected minimal a−total movement around the interference-connectivity distances s, v equal to 1 λ .

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On Multi-round Sensor Deployment for Barrier Coverage

Cited by 13 publications

References 11 publications

Weak Coverage of a Rectangular Barrier

Weak Coverage of a Rectangular Barrier

On the displacement for covering a d-dimensional cube with randomly placed sensors

On the Energy in Displacement of Random Sensors for Connectivity and Interference

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