Location-based matching in publish/subscribe revisited

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.