Title
Enhancing reliability of sensor networks by fine tuning their event observation behavior
Abstract
Sensor Networks are envisioned to be used in large variety of applications - health care, homeland security etc. - which require high reliability. Due to the fact that the sensors need to be low cost they have only scarce resources leading to a certain level of failures of sensor nodes or sensing devices attached to the nodes. For the applications mentioned reliable and fault tolerant sensor networks are in great demand. Available fault tolerant solutions are mainly customized approaches that revealed several shortcomings. We present an event specification language that allows configuring the level of reliability of a certain sensor network. It explicitly regards heterogeneous sensing capabilities and allows defining complex events as well as tailor made voting schemes. Features for multi-event detection facets and for fine-grained event-related fault tolerance are also part of the language. Our approach significantly enhances service and maintenance features and enables online configuration of sensor networks.
Year
DOI
Venue
2008
10.1109/WOWMOM.2008.4594886
Newport Beach, CA
Keywords
Field
DocType
sensor networks,high reliability,sensor node,enhancing reliability,event observation behavior,available fault tolerant solution,sensor network,event specification language,fine-grained event-related fault tolerance,certain level,fault tolerant sensor network,certain sensor network,fault tolerant,sensors,fault tolerance,specification language,computer vision,fault trees,fault detection,health care,voting,terrorism,wireless sensor networks,homeland security,face detection,reliability
Specification language,Key distribution in wireless sensor networks,Computer science,Fault detection and isolation,Soft sensor,Computer network,Fault tolerance,Face detection,Fault tree analysis,Wireless sensor network,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-4244-2100-8
1
0.36
References 
Authors
12
2
Name
Order
Citations
PageRank
Steffen Ortmann1154.61
Peter Langendoerfer222925.02