Resilient data-centric storage in wireless ad-hoc sensor networks

Abhishek Ghose, Jens Grossklags, John Chuang

Publikation: Beitrag in Buch/Bericht/KonferenzbandKapitelBegutachtung

70 Zitate (Scopus)

Abstract

Wireless sensor networks will be used in a wide range of challenging applications where numerous sensor nodes are linked to monitor and report distributed event occurrences. In contrast to traditional communication networks, the single major resource constraint in sensor networks is power, due to the limited battery life of sensor devices. It has been shown that data-centric methodologies can be used to solve this problem efficiently. In data-centric storage, a recently proposed data dissemination framework, all event data is stored by type at designated nodes in the network and can later be retrieved by distributed mobile access points in the network. In this paper we propose Resilient Data-Centric Storage (R-DCS) as a method to achieve scalability and resilience by replicating data at strategic locations in the sensor network. Through analytical results and simulations, we show that this scheme leads to significant energy savings in reasonably large-sized networks and scales well with increasing node-density and query rate. We also show that R-DCS realizes graceful performance degradation in the presence of clustered as well as isolated node failures, hence making the sensornet data robust.

OriginalspracheEnglisch
TitelLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Redakteure/-innenMing-Syan Chen, Panos K. Chrysanthis, Morris Sloman, Arkady Zaslavsky
Herausgeber (Verlag)Springer Verlag
Seiten45-62
Seitenumfang18
ISBN (Print)3540003932, 9783540003939
DOIs
PublikationsstatusVeröffentlicht - 2003
Extern publiziertJa

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band2574
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

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