Distributed subscriptions clustering with limited knowledge sharing for content-based publish/subscribe systems

One of the main issues in content-based publish/subscribe (CBPS) systems is how to dynamically determine groups of similar subscriptions to be adopted for exploiting efficient multicast techniques while guaranteeing at the same time the expressiveness of the subscription scheme. In this work, we propose a distributed mechanism which aims at satisfying important requirements of CBPS systems, that are: i) to guarantee the expressiveness of the subscription languages typical of the content-based paradigm, ii) to exploit efficient events dissemination, iii) to maintain the system scalability in terms of nodes and subscriptions, iv) to start an adaptive system reconfiguration despite new incoming subscriptions. One of the main feature of the proposed mechanism is the use of the system state knowledge sharing by system nodes, with the goal of limiting the system overhead in terms of computing, bandwidth and storage resources. Through a set of simulations we demonstrate the efficiency of the proposed solution.