Sensor stream reduction for clustered wireless sensor networks
Proceedings of the 2008 ACM symposium on Applied computing
An in-network reduction algorithm for real-time wireless sensor network applications
Proceedings of the 4th ACM workshop on Wireless multimedia networking and performance modeling
On using provenance data to increase the reliability of ubiquitous computing environments
Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Efficient querying of distributed provenance stores
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Facilitating fine grained data provenance using temporal data model
Proceedings of the Seventh International Workshop on Data Management for Sensor Networks
The Foundations for Provenance on the Web
Foundations and Trends in Web Science
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Sensor network data has both historical and realtime value. Making historical sensor data useful, in particular, requires storage, naming, and indexing. Sensor data presents new challenges in these areas. Such data is location-specific but also distributed; it is collected in a particular physical location and may be most useful there, but it has additional value when combined with other sensor data collections in a larger distributed system. Thus, arranging location-sensitive peer-to-peer storage is one challenge. Sensor data sets do not have obvious names, so naming them in a globally useful fashion is another challenge. The last challenge arises from the need to index these sensor data sets to make them searchable. The key to sensor data identity is provenance, the full history or lineage of the data. We show how provenance addresses the naming and indexing issues and then present a research agenda for constructing distributed, indexed repositories of sensor data.