Using event detection latency to evaluate the coverage of a wireless sensor network

Wang, You‐Chiun; Cheng, Kai-Yang; Tseng, Yu–Chee

doi:10.1016/j.comcom.2007.05.009

Cited by 11 publications

(4 citation statements)

References 22 publications

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“…Wang et al [11] analyzed detection latency using a probabilistic approach for k-sensor detection model and considered latency as a performance metric for detection. Zhu and Ni [13] first formalized the QoS provisioning problem in event detection applications in WSNs.…”

Section: Related Workmentioning

confidence: 99%

QoS Support in Event Detection in WSN through Optimal k-Coverage

Alam

Karmakar

Murshed

et al. 2011

Procedia Computer Science

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Wireless sensor networks promise to guarantee accurate, fault tolerant and timely detection of events in large scale sensor fields. To achieve this the notion of k-coverage is widely employed in WSNs where significant redundancy is introduced in deployment as an event is expected to be sensed by at least k sensors in the neighborhood. As sensor density increases significantly with k, it is imperative to find the optimal k for the underlying event detection system. In this work, we consider the detection probability, fault tolerance and latency as the Quality of Service (QoS) metrics of an event detection system employing k-coverage and present a probabilistic model to guarantee given QoS support with the minimum degree of coverage taking into account the noise related measurement error, communication interference and sensor fault probability. This work eventually resolves the problem of over or under deployment of sensors, increases scalability and provides a well defined mechanism to tune the degree of coverage according to performance needs.

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Section: Related Workmentioning

confidence: 99%

QoS Support in Event Detection in WSN through Optimal k-Coverage

Alam

Karmakar

Murshed

et al. 2011

Procedia Computer Science

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“…Many related research works on event delay in the eventdriven WSNs have been done in past years. Wang et al [5] assumed an event can be detected successfully with a probability p in working state, and used a probabilistic approach to analyze the detection event delay under the anysensor-detection model and the k-sensor-detection model respectively. Bouabdallah et al [6] analyzed the latencylifetime tradeoff in the WSN with multiple source nodes, and thus derived the optimal number of source node under several limited factors.…”

Section: Related Workmentioning

confidence: 99%

“…Integrating Eqs. (1), (5), and (6), the total average event delay through a route path in WSNs is given as follows:…”

Section: B Analysis Of the Delay Through A Route Pathmentioning

confidence: 99%

Analysis on Event Delay in Event-Driven Wireless Sensor Networks

Zhou¹,

Li²,

Zhang³

2012

Proceedings of 2012 National Conference on Information Technology and Computer Science

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In this paper, we consider an event-driven wireless sensor network (WSN) scenario, in which the events arrive with a certain probability in a time of interval. Firstly, we analyze the event delay in a single node in an M/G/1 vacation queueing model. Then, considering the limited buffer space, channel contention and the possibility of a link failure, we derive the total average event delay through a route path. Finally, we build an OMNeT++ simulation and verify our theoretical research results. This research work should provide a guidance for understanding the event delay and future designing more flexible event-driven WSN routing protocols.

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“…[2] analyzes event detection delay in WSNs. [3] uses the event detection latency to evaluate the coverage of wireless sensor networks.…”

Section: Introductionmentioning

confidence: 99%

Event detection and channel allocation in cognitive radio sensor networks

Jamal

Tham

Wong

2012

2012 IEEE International Conference on Communication Systems (ICCS)

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Emerging applications of wireless sensor networks require accurate event detection while coping with in-network congestion, delay, power and probability of false alarm (PFA) constraints. Dynamic spectrum access stands as a promising and spectrum-efficient communication approach for resourceconstrained wireless sensor networks. In this paper, we propose a two tier sensor network where the lower tier comprises a multi-hop sensor network with a secondary user (SU) as a cluster head, and the upper tier consists of a network of secondary users competing for spectrum in order to relay their messages to the sink node. The lower tier is therefore responsible for accurately detecting an event, whereas the upper tier is responsible for relaying the detection to the sink node efficiently. We incorporated two Constrained Markov Decision Processes (CMDP): one for accurately detecting an event while satisfying delay, PFA and congestion constraints by adjusting the detection criterion, and the other for allocating the best available spectrum to the SU on a priority basis.

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Using event detection latency to evaluate the coverage of a wireless sensor network

Cited by 11 publications

References 22 publications

QoS Support in Event Detection in WSN through Optimal k-Coverage

QoS Support in Event Detection in WSN through Optimal k-Coverage

Analysis on Event Delay in Event-Driven Wireless Sensor Networks

Event detection and channel allocation in cognitive radio sensor networks

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