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
The Claremont report on database research
ACM SIGMOD Record
Efficient event processing through reconfigurable hardware for algorithmic trading
Proceedings of the VLDB Endowment
GPX-matcher: a generic boolean predicate-based XPath expression matcher
Proceedings of the 14th International Conference on Extending Database Technology
Towards vulnerability-based intrusion detection with event processing
Proceedings of the 5th ACM international conference on Distributed event-based system
High performance content-based matching using GPUs
Proceedings of the 5th ACM international conference on Distributed event-based system
Towards an extensible efficient event processing kernel
PhD '12 Proceedings of the on SIGMOD/PODS 2012 PhD Symposium
Relevance Matters: Capitalizing on Less (Top-k Matching in Publish/Subscribe)
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
High-performance location-aware publish-subscribe on GPUs
Proceedings of the 13th International Middleware Conference
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Event processing is gaining rising interest in industry and in academia. The common application pattern is that event processing agents publish events while other agents subscribe to events of interest. Extensive research has been devoted to developing efficient and scalable algorithms to match events with subscribers' interests. The predominant abstraction used in this context is the content-based publish/subscribe (pub/sub) paradigm for modeling an event processing application. Applications that have been referenced in this space include emerging applications in co-spaces that rely on location-based information [1, 7], algorithmic trading and (financial) data dissemination [13], and intrusion detection system [4]. In this work, we focus primarily on the role of state-of-the-art matching algorithms in location-based pub/sub applications.