Embedding the Internet: introduction
Communications of the ACM
Distributed Algorithms
The Impact of Data Aggregation in Wireless Sensor Networks
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
Report from the first workshop on geo sensor networks
ACM SIGMOD Record
Power-conserving computation of order-statistics over sensor networks
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
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
Design and Analysis of Distributed Algorithms (Wiley Series on Parallel and Distributed Computing)
Design and Analysis of Distributed Algorithms (Wiley Series on Parallel and Distributed Computing)
Effect of Neighborhood on In-Network Processing in Sensor Networks
GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
COSIT'11 Proceedings of the 10th international conference on Spatial information theory
A unified framework for decentralized reasoning about gradual changes in topological relations
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Exploiting qualitative spatial reasoning for topological adjustment of spatial data
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
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This paper proposes an efficient, decentralized algorithm for determining the topological relationship between two regions monitored by a geosensor network. Many centralized algorithms already exist for this purpose (used for example in spatial databases). However, these algorithms are not suited to decentralized spatial computing environments, like geosensor networks, which must operate without global knowledge of the system state and without centralized control. Unlike many existing decentralized spatial algorithms, the proposed algorithm is also able to operate in the absence of information about a node's coordinate location. This makes the algorithm suitable for applications of geosensor networks where GPS or other positioning systems are unavailable or unreliable. The algorithm approach is founded on the well-known 4-intersection model, using in-network data aggregation and spatial filtering (involving nodes only at some region boundaries). This ensures only a relatively small proportion of the network is involved in computation, thus increasing efficiency. Our analysis shows that while the overall communication complexity of the algorithm is O(n), the load balancing is optimal leading to a constant O(1) communication complexity for individual nodes. This expectation is confirmed with empirical investigation using simulation, which demonstrates the practical efficiency of the algorithm.