Transforming Area Coverage to Target Coverage to Maintain Coverage and Connectivity for Wireless Sensor Networks

Deng, Xiu; Yu, Jiguo; Yu, Dongxiao; Chen, Congcong

doi:10.1155/2012/254318

Cited by 12 publications

(6 citation statements)

References 18 publications

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“…The author also used a greedy method for assures coverage and connectivity in WSN. In [15], the author presented how energy consumption is reduced in area coverage problem by looking at the boundary effects in a new point of view.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Deployment Model for Target Coverage in Wireless Sensor Network

Subramanian¹,

Shanmugavel²

2023

Intelligent Automation &Amp; Soft Computing

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Target coverage and continuous connection are the major recital factors for Wireless Sensor Network (WSN). Several previous research works studied various algorithms for target coverage difficulties; however they lacked to focus on improving the network's life time in terms of energy. This research work mainly focuses on target coverage and area coverage problem in a heterogeneous WSN with increased network lifetime. The dynamic behavior of the target nodes is unpredictable, because the target nodes may move at any time in any direction of the network. Thus, target coverage becomes a major problem in WSN and its applications. To solve the issue, this research work is motivated to design and develop an intelligent model named Distributed Flexible Wheel Chain (DFWC) model for efficient target coverage and area coverage in WSN applications. More number of target nodes is covered by minimum number of sensor nodes that can improve energy efficiency. To be specific, DFWC motivated at obtaining lesser connected target coverage, where every target is available in the monitoring area is covered by a smaller number of sensor nodes. The simulation results show that the proposed DFWC model outperforms the existing models with improved performance.

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Section: Related Workmentioning

confidence: 99%

Intelligent Deployment Model for Target Coverage in Wireless Sensor Network

Subramanian¹,

Shanmugavel²

2023

Intelligent Automation &Amp; Soft Computing

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“…Hence, area coverage [24] means that every point inside a xed area must be monitored, while target coverage [38] refers to the objective of coverage for a nite number of discrete points called targets, and barrier coverage [11,17] focuses on preventing intruders from entering into the region of interest. In [8] authors transform the area coverage problem into the target coverage one, taking into account the intersection points among disks of sensors nodes or between disks of sensor nodes and boundaries. In [12] authors prove that if the perimeters of the sensors are suciently covered it will be the case for the whole area.…”

Section: Related Literaturementioning

confidence: 99%

Perimeter-based coverage optimization to improve lifetime in wireless sensor networks

Idrees

Deschinkel

Salomon

et al. 2016

Engineering Optimization

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The most important problem in a Wireless Sensor Network (WSN) is to optimize the use of its limited energy provision, so that it can fulll its monitoring task as long as possible. Among known available approaches that can be used to improve power management, lifetime coverage optimization provides activity scheduling which ensures sensing coverage while minimizing the energy cost. In this paper an approach called Perimeterbased Coverage Optimization protocol (PeCO) is proposed. It is a hybrid of centralized and distributed methods : the region of interest is rst subdivided into subregions and the protocol is then distributed among sensor nodes in each subregion. The novelty of the approach lies essentially in the formulation of a new mathematical optimization model based on the perimeter coverage level to schedule sensors' activities. Extensive simulation experiments demonstrate that PeCO can oer longer lifetime coverage for WSNs compared to other protocols.

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“…They attempt to partition sensors into a maximum number of set covers that guarantee full targets coverage. In [ 31 ], Deng et al discussed the energy-efficient area coverage problem considering boundary effects in a new perspective.…”

Section: Related Workmentioning

confidence: 99%

On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks

Chen

et al. 2016

Sensors

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Coverage and connectivity are two important performance evaluation indices for wireless sensor networks (WSNs). In this paper, we focus on the connected target k-coverage (CTCk) problem in heterogeneous wireless sensor networks (HWSNs). A centralized connected target k-coverage algorithm (CCTCk) and a distributed connected target k-coverage algorithm (DCTCk) are proposed so as to generate connected cover sets for energy-efficient connectivity and coverage maintenance. To be specific, our proposed algorithms aim at achieving minimum connected target k-coverage, where each target in the monitored region is covered by at least k active sensor nodes. In addition, these two algorithms strive to minimize the total number of active sensor nodes and guarantee that each sensor node is connected to a sink, such that the sensed data can be forwarded to the sink. Our theoretical analysis and simulation results show that our proposed algorithms outperform a state-of-art connected k-coverage protocol for HWSNs.

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Transforming Area Coverage to Target Coverage to Maintain Coverage and Connectivity for Wireless Sensor Networks

Cited by 12 publications

References 18 publications

Intelligent Deployment Model for Target Coverage in Wireless Sensor Network

Intelligent Deployment Model for Target Coverage in Wireless Sensor Network

Perimeter-based coverage optimization to improve lifetime in wireless sensor networks

On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks

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