In this paper, we are concerned about content-based networking (CBN) at extreme scales, characterized by a large number of widely spread consumers, heterogeneous consumer requirements, huge volume of publications, and the scarcity of end-to-end bandwidth. We extend CBN with a generic service model that allows consumers to express their interests in future publications including cached content, but also to quantify the maximum amount of information they are willing to consume. We take advantage of this knowledge to pace the dissemination process and therefore, enhance the service efficiency. Early evaluation results show gains of up to 80% compared to a baseline CBN model.

Content-based publish/subscribe systems provide a useful alternative to traditional address-based communication due to their ability to decouple communication between participants. It has remained a challenge to design a scalable overlay supporting the complexity of content-based networks, while satisfying the desirable properties large distributed systems should have. This paper presents the design of Mirinae, a new structured peer-to-peer overlay mesh based on the interests of peers. Given an event, Mirinae provides a flexible and efficient dissemination tree minimizing the participation of non-matching nodes. We also present a novel ID space transformation mechanism for balancing routing load of peers even with highly skewed data, which is typical of the real world. Our evaluation demonstrates that Mirinae is able to achieve its goals of scalability, efficiency, and near-uniform load balancing. Mirinae can be used as a substrate for content-search and range query in other important distributed applications.