A random projection approach to subscription covering detection in publish/subscribe systems

Authors:
Duc A. Tran;Thinh Nguyen
Affiliations:
Department of Computer Science, University of Massachusetts, Boston, 02125, USA;Department of Electrical and Computer Engineering, Oregon State University, Corvallis, 97331, USA
Venue:
COLCOM '07 Proceedings of the 2007 International Conference on Collaborative Computing: Networking, Applications and Worksharing
Year:
2007

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Approximate covering detection among content-based subscriptions using space filling curves

Journal of Parallel and Distributed Computing

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Abstract

Subscription covering detection is useful to improving the performance of any publish/subscribe system. However, an exact solution to querying coverings among a large set of subscriptions in high dimension is computationally too expensive to be practicable. Therefore, we are interested in an approximate approach. We focus on spherical subscriptions and propose a solution based on random projections. Our complexities are substantially better than that of the exact approach. The proposed solution can potentially find exact coverings with a success probability 100% asymptotically approachable.