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SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
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OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
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IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
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CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
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FAST'05 Proceedings of the 4th conference on USENIX Conference on File and Storage Technologies - Volume 4
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MobiDE '07 Proceedings of the 6th ACM international workshop on Data engineering for wireless and mobile access
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MDM '07 Proceedings of the 2007 International Conference on Mobile Data Management
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ADHOC-NOW '08 Proceedings of the 7th international conference on Ad-hoc, Mobile and Wireless Networks
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Proceedings of the 6th ACM international symposium on Mobility management and wireless access
Perimeter discovery in wireless sensor networks
Journal of Parallel and Distributed Computing
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Mobile Information Systems
In-network data acquisition and replication in mobile sensor networks
Distributed and Parallel Databases
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This paper assumes a set of n mobile sensors that move in the Euclidean plane as a swarm. Our objectives are to explore a given geographic region by detecting and aggregating spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in environments where the user (i.e., the sink) is infrequently within communication range from the field deployment. Our framework, coined SenseSwarm, dynamically partitions the sensing devices into perimeter and core nodes. Data acquisition is scheduled at the perimeter in order to minimize energy consumption while storage and replication takes place at the core nodes which are physically and logically shielded to threats and obstacles. To efficiently identify the perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a message complexity of O(p + n), where p denotes the number of nodes on the perimeter and n the overall number of nodes. For storage and replication we devise a spatio-temporal in-network aggregation scheme based on minimum bounding rectangles and minimum bounding cuboids. Our trace-driven experimentation shows that our framework can offer significant energy reductions while maintaining high data availability rates.