Coverage Contribution Area Based $k$ -Coverage for Wireless Sensor Networks

Yu, Jiguo; Wan, Shengli; Cheng, Xiuzhen; Yu, Dongxiao

doi:10.1109/tvt.2017.2681692

Cited by 110 publications

(74 citation statements)

References 27 publications

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“…Based on the requirement, coverage can be classified into three main categories: area coverage, point coverage, and barrier coverage [1,[20][21][22].…”

Section: Wsn Coverage Issuementioning

confidence: 99%

The Coverage Issues in WSNs

Rani

Anand

2020

ARJOM

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Aim: Wireless Sensor Networks is one of the hot research topic in previous years due to its wide contribution in emerging industry that is Internet of Things. A wireless sensor network is a network of tiny devices, which can gather the information from surrounding and then successfully communicate it via wireless link. WSNs are widely used for monitoring targets in given field of interest. Most popular area of research in Wireless Sensor Networks is coverage. This paper focus on coverage issues in Wireless Sensor Networks. Study Design: Various Issues in WSNs being studied and analyzed. Place and Duration of Study: Swami Parmanand College Lalru, between May 2019 to December 2019. Methodology: It included following steps:- Survey of the literature related to the proposed work. Comparison of different types of WSNs and challenges and issues related to them. Detailed study of coverage issue involved in implementation of WSN. Results: Coverage selection depends on the system requirement. Each coverage has its own advantages and disadvantages related to its implementation. “Table 2: Comparison between Various WSN and challenges related to them” it discusses about various types of WSNs and the challenges related to each one of them. Conclusion: Coverage in WSNs can be defined on how well the sensor nodes monitor the targets in given field of interest. Each application comes with different set of coverage requirements; hence, deployment strategies are chosen based on the requirements.

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“…Based on the requirement, coverage can be classified into three main categories: area coverage, point coverage, and barrier coverage [1,[20][21][22].…”

Section: Wsn Coverage Issuementioning

confidence: 99%

The Coverage Issues in WSNs

Rani

Anand

2020

ARJOM

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“…In order to estimate the probabilistic area coverage in WSN, the authors in [ 30 ] find the relationship between the coverage of two adjacent points and transform the full area coverage problem into a point coverage problem for the K -coverage configuration. In [ 31 ], the K -coverage problem of WSN is handled by considering the Coverage Contribution Area (CCA) as a parameter to prolong the network lifetime. In [ 32 ], the network connectivity of the K -coverage sensors is addressed, and the K -coverage scheduling protocol is designed to ensure that at least K number of active sensors stays connected in each round.…”

Section: Related Workmentioning

confidence: 99%

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

Sahoo

Thakkar

Hwang

2017

Sensors

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The K-coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K-covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) and Self-Organized K-coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized.

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“…Broadcasting is a fundamental function for many services in wireless sensor networks (WSNs) [1,2], such as data collection, code updating, and topology discovering [3][4][5][6]. Many effective broadcasting algorithms have been investigated to improve the network performance, while the total number of transmissions is often taken as a measured metric.…”

Section: Introductionmentioning

confidence: 99%

“…As this working mode is much different, the MTB problem in duty-cycled wireless sensor networks needs to be reinvestigated and the following two issues should be addressed: (1) A node may need several transmissions to inform all its neighbors since the neighbors may be active at different time slots. (2) How to construct the broadcast tree to exploit nodes' multiple active time slots for scheduling is also a big challenge. In duty-cycled wireless networks, the MTB problem is mainly studied by [18][19][20][21] currently.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Broadcast Scheduling Algorithm in Duty-Cycled Multihop Wireless Networks

Chen

Wang

Cheng

et al. 2019

Wireless Communications and Mobile Computing

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Broadcasting is a fundamental function for disseminating messages in multihop wireless networks. Minimum-Transmission Broadcasting (MTB) problem aims to find a broadcast schedule with minimum number of transmissions. Previous works on MTB in duty-cycled networks exploit a rigid assumption that nodes have only active time slot per working cycle. In this paper, we investigated the MTB problem in duty-cycled networks where nodes are allowed arbitrary active time slots per working cycle (MTBDCA problem). Firstly, it is proved to be NP-hard and (ln Δ)-inapproximable, where Δ is the maximum degree in the network. Secondly, an auxiliary graph is proposed to integrate nodes' active time slots into the network and a novel covering problem is proposed to exploit nodes' multiple active time slots for scheduling. Then, a ln(Δ + 1)-approximation algorithm is proposed for MTBDCA and a (ln(Δ + 1) + Δ)-approximation algorithm is proposed for all-to-all MTBDCA. Finally, extensive experimental results demonstrate the efficiency of the proposed algorithm.

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Coverage Contribution Area Based $k$ -Coverage for Wireless Sensor Networks

Cited by 110 publications

References 27 publications

The Coverage Issues in WSNs

The Coverage Issues in WSNs

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

Energy-Efficient Broadcast Scheduling Algorithm in Duty-Cycled Multihop Wireless Networks

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