Exploring link correlation for efficient flooding in wireless sensor networks

Ting Zhu, Ziguo Zhong, Tian He, Zhi Li Zhang

Research output: Contribution to conferencePaperpeer-review

17 Scopus citations

Abstract

Existing flooding algorithms have demonstrated their effectiveness in achieving communication efficiency and reliability in wireless sensor networks. However, fur− ther performance improvement has been hampered by the assumption of link independence, a design premise imposing the need for costly acknowledgements (ACKs) from every receiver. In this paper, we present Collec− tive Flooding (CF), which exploits the link correlation to achieve flooding reliability using the concept of collective ACKs. CF requires only 1−hop information from a sender, making the design highly distributed and scalable with low complexity. We evaluate CF extensively in real− world settings, using three different types of testbeds: a single hop network with 20 MICAz nodes, a multi− hop network with 37 nodes, and a linear outdoor net− work with 48 nodes along a 326−meter−long bridge. Sys− tem evaluation and extensive simulation show that CF achieves the same reliability as the state−of−the art solu− tions, while reducing the total number of packet trans− mission and dissemination delay by 30 ∼ 50% and 35 ∼ 50%, respectively.

Original languageEnglish (US)
Pages49-63
Number of pages15
StatePublished - 2010
Event7th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2010 - San Jose, United States
Duration: Apr 28 2010Apr 30 2010

Conference

Conference7th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2010
CountryUnited States
CitySan Jose
Period4/28/104/30/10

Bibliographical note

Funding Information:
This work was supported in part by NSF grants CNS? 0917097, CNS?0845994, and CNS?0626609. We also received partial support from InterDigital and Microsoft Research. We thank our shepherd Dr. Philip Levis and the reviewers for their valuable comments.

Funding Information:
This work was supported in part by (-F grants C(-− 0917097, C(-−0845994, and C(-−0626609. We also received partial support from InterDigital and Microsoft Research. We thank our shepherd Dr. Philip Levis and the reviewers for their valuable comments.

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