LATEX DSL: A Coverage Control Protocol for heterogeneous Wireless Sensor Networks

Wang, Huanzhao; Dong, Bei; Chen, Peijun; Qian, Chen; Kong, Junjun

doi:10.1109/icsnc.2007.48

Cited by 4 publications

(2 citation statements)

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“…6) Network scalability: Coverage control algorithm must consider the network node scalability [7]. 7) Algorithm implementation strategy: Need to design a simple and efficient distributed wireless sensor network coverage control algorithm [8].…”

Section: Performance Evaluations For Hwsn Coverage Algorithmmentioning

confidence: 99%

Research on HWSN Node Covering Algorithm

Yao

2014

AMM

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This paper first introduces the types and characteristics of HWSN, expounds its typical architecture, through comparing with homogeneous wireless sensor network, the performance of HWSN is quantitative calculated, analysis results show that HWSN can improve the reliability of data transmission, reduce the energy consumption of data transmission, reduce the delay of data transmission, and with the increase of network scale, highlight the advantages of heterogeneous networks. HWSN covering algorithm performance evaluation indexes are given finally.

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Section: Performance Evaluations For Hwsn Coverage Algorithmmentioning

confidence: 99%

Research on HWSN Node Covering Algorithm

Yao

2014

AMM

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“…That is, the service should continuously provide every node a fresh overview on the percentage of each sensor type over available nodes in its cluster. This information can be used in coverage control services [6] in order to provide stable sensing capability by rescheduling sleep mode [7] at run time. It can also provide useful information for the redeployment of a particular sensor, regarding application requirements.…”

Section: Introductionmentioning

confidence: 99%

Gossip-based density estimation in dynamic heterogeneous sensor networks

Malazi

Zamanifar

Pruteanu

et al. 2011

2011 7th International Wireless Communications and Mobile Computing Conference

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Abstract-The density estimation of diverse sensor types in a heterogeneous sensor network is a useful and challenging service that can be applied in clustering schemes, node redeployment, and sleep mode scheduling. Energy efficiency is one of the main requirements for any wireless sensor network service. Besides, the service has to provide a fresh version of the estimation to each node. Network dynamics, especially node mobility, introduce new challenges. Moreover, churn makes the problem even more complicated. In this paper we introduce a gossip-based approach for the density estimation of sensor diversity in clustered dynamic networks. The devised method supports node mobility and churn, as well as redeployment of new nodes. It is fully distributed and adaptive to network dynamics. We analyze the effect of mobility as well as scalability in the number of clusters and the quantity of nodes. Our algorithm has a fast convergence speed and provides more accurate estimation compared to similar approaches.

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