A coverage-aware clustering protocol for wireless sensor networks

Wang, Bang; Lim, Hyuk; Ma, Di

doi:10.1016/j.comnet.2012.01.016

Cited by 60 publications

(18 citation statements)

References 17 publications

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“…However, the TDSFK scheme has to pay the energy consumption for the state transition which is given less consideration by the previous studies. The authors of [5] noticed that the processors and sensors for the state transition need certain energy. They also pointed out that the Mica mote sensor requires 4 ms to start [5].…”

mentioning

confidence: 99%

“…The authors of [5] noticed that the processors and sensors for the state transition need certain energy. They also pointed out that the Mica mote sensor requires 4 ms to start [5]. Hence, how to optimize the given sensing frequency of node to increase the lifetime and improve the monitoring quality is an important research issue.…”

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confidence: 99%

“…The quality of target detection mainly includes the delay for detection, the probability of missing target and network lifetime. Wu et al [5] pointed out that in WSNs, node wakes up periodically to detect the target, receive or send data to the sink or the next-hop node. After that, it will re-enter the sleep mode.…”

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confidence: 99%

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Mobile Target Detection in Wireless Sensor Networks With Adjustable Sensing Frequency

Dong

Ota

et al. 2016

IEEE Systems Journal

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Abstract-How to sense and monitor the environment with high quality is an important research subject in the Internet of Things (IOT). This paper deals with an important issue of the balance between the quality of target detection and lifetime in Wireless Sensor Networks (WSNs). Two target monitoring schemes are proposed. One is TDSFK (Target Detection with Sensing Frequency K) which distributes the sensing time that currently is only on a portion of the sensing period into the entire sensing period. That is, the sensing frequency increases from 1 to K. The other scheme is TDASF (Target Detection with Adjustable Sensing Frequency) which adjust the sensing frequency on those nodes which have residual energy. The simulation results show that the TDASF scheme can improve the network lifetime by more than 17.4%, and can reduce the weighted detection delay by more than 101.6%.

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confidence: 99%

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Mobile Target Detection in Wireless Sensor Networks With Adjustable Sensing Frequency

Dong

Ota

et al. 2016

IEEE Systems Journal

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“…To aid this claim, extensive simulations on 90 homogeneous and heterogeneous WSN models are evaluated and compared from the LEACH, SEP, and one of many existing evolutionary-based routing protocols, hierarchical clustering-algorithm-based genetic algorithm (HCR). Wang, Bang [5] provided a computation method for the perfect cluster size to minimize the average energy consumption rate per unit area. In the proposed coverageaware clustering protocol, they defined a cost metric that favors those nodes being more energy-redundantly covered as better candidates for cluster heads and select active nodes in ways that tries to emulate the absolute most efficient tessellation for area coverage.…”

Section: Pasccc: Priority-based Application-specific Congestion Contrmentioning

confidence: 99%

A Study of Congestion Control Protocols for Wireless Sensor Networks

Singh¹,

Singh²

2015

IJCA

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Within the last couple of years a comparatively large amount of clustering routing protocols have already been developed for WSNs. This paper is an effort to comprehensively review and critically discuss the absolute most prominent clustering routing algorithms which have been developed for WSNs. The goals with this survey are to produce a large audience conscious of the existence and of the usually good performance of numerous clustering routing protocols in WSNs. From the survey, it has been discovered that none of technique performs effectively in most fields. Therefore the paper ends with the future scope to overcome these issues.

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“…The related technique-efficient issues, such as clustering routing, topology control, and multihop transmission, are widely used to improve energy efficiency for WSNs [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. On the other hand, it is very important to note that hybridization combination of various approaches may affect total performance.…”

Section: Introductionmentioning

confidence: 99%

Evidence-Efficient Multihop Clustering Routing Scheme for Large-Scale Wireless Sensor Networks

Xin

2017

Wireless Communications and Mobile Computing

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Energy consumption and transmission reliability are the most common issues in wireless sensor networks (WSNs). By studying the broadcast nature of data transmission in WSNs, the mechanism of guaranteeing reliable transmission is abstracted as propagation of responsibility and availability. The responsibility and availability represent the accumulated evidence of nodes to support reliable transmission. Based on the developed mechanism, an evidence-efficient cluster head rotation strategy and algorithm are presented. Furthermore, backbone construction algorithm is studied to generate the minimum aggregation tree inside the candidate cluster heads. A minimum aggregation tree-based multihop routing scheme is also investigated, which allows the elected cluster heads to choose the optimally main path to forward data locally and dynamically. As a hybridization of the above, an evidence-efficient multihop clustering routing (EEMCR) method is proposed. The EEMCR method is simulated, validated, and compared with some previous algorithms. The experimental results show that EEMCR outperforms them in terms of prolonging network lifetime, improving transmission reliability, postponing emergence of death nodes, enhancing coverage preservation, and degrading energy consumption.

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A coverage-aware clustering protocol for wireless sensor networks

Cited by 60 publications

References 17 publications

Mobile Target Detection in Wireless Sensor Networks With Adjustable Sensing Frequency

Mobile Target Detection in Wireless Sensor Networks With Adjustable Sensing Frequency

A Study of Congestion Control Protocols for Wireless Sensor Networks

Evidence-Efficient Multihop Clustering Routing Scheme for Large-Scale Wireless Sensor Networks

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