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

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.