Index structures for selective dissemination of information under the Boolean model
ACM Transactions on Database Systems (TODS)
Matching events in a content-based subscription system
Proceedings of the eighteenth annual ACM symposium on Principles of distributed computing
Filtering algorithms and implementation for very fast publish/subscribe systems
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Design and evaluation of a wide-area event notification service
ACM Transactions on Computer Systems (TOCS)
Efficient filtering in publish-subscribe systems using binary decision diagrams
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
Query Merging: Improving Query Subscription Processing in a Multicast Environment
IEEE Transactions on Knowledge and Data Engineering
Efficient Filtering of XML Documents for Selective Dissemination of Information
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Forwarding in a content-based network
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Evaluating Advanced Routing Algorithms for Content-Based Publish/Subscribe Systems
MASCOTS '02 Proceedings of the 10th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
Modeling Uncertainties in Publish/Subscribe Systems
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
AGILE: adaptive indexing for context-aware information filters
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Opportunistic overlays: efficient content delivery in mobile ad hoc networks
Proceedings of the ACM/IFIP/USENIX 2005 International Conference on Middleware
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Efficient subsumption checking, deciding whether a subscription or publication is covered by a set of previously defined subscriptions, is of paramount importance for publish/subscribe systems. It provides the core system functionality—matching of publications to subscriber needs expressed as sub-scriptions—and additionally, reduces the overall system load and generated traffic since the covered subscriptions are not propagated in distributed environments. As the subsumption problem was shown previously to be co-NP complete and existing solutions typically apply pairwise comparisons to detect the subsumption relationship, we propose a ‘Monte Carlo type' probabilistic algorithm for the general subsumption problem. It determines whether a publication/subscription is covered by a disjunction of subscriptions in O(k m d), where k is the number of subscriptions, m is the number of distinct attributes in subscriptions, and d is the number of tests performed to answer a subsumption question. The probability of error is problem-specific and typically very small, and sets an upper bound on d. Our experimental results show significant gains in term of subscription set reduction which has favorable impact on the overall system performance as it reduces the total computational costs and networking traffic. Furthermore, the expected theoretical bounds underestimate algorithm performance because it performs much better in practice due to introduced optimizations, and is adequate for fast forwarding of subscriptions in case of high subscription rate.