Matching events in a content-based subscription system
Proceedings of the eighteenth annual ACM symposium on Principles of distributed computing
Habitat monitoring: application driver for wireless communications technology
SIGCOMM LA '01 Workshop on Data communication in Latin America and the Caribbean
Design and evaluation of a wide-area event notification service
ACM Transactions on Computer Systems (TOCS)
A Constant-Factor Approximation Algorithm for the Multicommodity
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Hermes: A Distributed Event-Based Middleware Architecture
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
Energy-efficient surveillance system using wireless sensor networks
Proceedings of the 2nd international conference on Mobile systems, applications, and services
ICNP '05 Proceedings of the 13TH IEEE International Conference on Network Protocols
A framework for event composition in distributed systems
Proceedings of the ACM/IFIP/USENIX 2003 International Conference on Middleware
Efficient filtering of composite events
BNCOD'03 Proceedings of the 20th British national conference on Databases
Multiobjective data clustering
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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Constructing optimal event correlation architecture is crucial to large-scale event services. It plays an instrumental role in detecting composite events requested by different subscribers in scalable and timely manner. However, events generated from different sources might have different time and priority requirements. In addition, the network links and correlation servers might have different bandwidth and processing constraints respectively. In this work, we address the problem of optimizing distributed event correlation to maximize the correlation profit (benefit minus shipping and processing cost) of detecting composite events, while at the same time satisfying the network bandwidth, node capacity, and correlation tasks time constrains. We show that this problem is NP-hard and provide a heuristic approximation algorithm. We evaluate our heuristic approach with different network sizes, topologies under different event delivery and detection requirements. Our simulation study shows that the results obtained by our heuristic are close to the upper bound.