Scaling Up Publish/Subscribe Overlays using Interest Correlation for Link Sharing

Miguel Matos, Pascal Felber, Rui Oliveira, José Orlando Pereira & Etienne Rivière

Résumé Topic-based publish/subscribe is at the core of many distributed systems, ranging from application integration middleware to news dissemination. Therefore, much research was dedicated to publish/subscribe architectures and protocols, and in particular to the design of overlay networks for decentralized topic-based routing and efficient message dissemination. Nonetheless, existing systems fail to take full advantage of shared interests when disseminating information, hence suffering from high maintenance and traffic costs, or construct overlays that cope poorly with the scale and dynamism of large networks. In this paper, we present StaN, a decentralized protocol that optimizes the properties of gossip-based overlay networks for topic-based publish/subscribe by sharing a large number of physical connections without disrupting its logical properties. StaN relies only on local knowledge and operates by leveraging common interests among participants to improve global resource usage and promote topic and event scalability. The experimental evaluation under two real workloads, both via a real deployment and through simulation, shows that StaN provides an attractive infrastructure for scalable topic-based publish/subscribe.
Mots-clés Subscriptions, Scalability, Clustering methods, link sharing, Publish and subscribe, scalability, topic-based, interest correlation, subscription clustering
Citation M. Matos, et al., "Scaling Up Publish/Subscribe Overlays using Interest Correlation for Link Sharing," IEEE Transactions on Parallel and Distributed Systems, vol. 12, p. 2462-2471, Jan. 2013.
Type Article de périodique (Anglais)
Date de publication 13-1-2013
Nom du périodique IEEE Transactions on Parallel and Distributed Systems
Volume 12
Pages 2462-2471
URL http://doi.ieeecomputersociety.org/10.1109/TPDS.2013.6