Abstract

Abstract

Abstract

Abstract
Traditional reliable broadcast protocols fail to scale to large settings. The paper proposes a reliable multicast protocol that integrates two approaches to deal with the large-scale dimension in group communication protocols: gossip-based probabilistic broadcast and semantic reliability. The aim of the resulting protocol is to improve the resiliency of the probabilistic protocol to network congestion by allocating scarce resources to semantically relevant messages. Although intuitively it seems that a straightforward combination of probabilistic and semantic reliable protocols is possible, we show that it offers disappointing results. Instead, we propose an architecture based on a specialized probabilistic semantically reliable layer and show that it produces the desired results. The combined primitive is thus scalable to large number of participants, highly resilient to network and process failures, and delivers a high quality data flow even when the load exceeds the available bandwidth. We present a summary of simulation results that compare different protocol configurations. © 2001 IEEE.

Abstract

Abstract
Unstructured peer-to-peer overlay networks are very resilient to churn and topology changes, while requiring little maintenance cost. Therefore, they are an infrastructure to build highly scalable large-scale services in dynamic networks. Typically, the overlay topology is defined by a peer sampling service that aims at maintaining, in each process, a random partial view of peers in the system. The resulting random unstructured topology is suboptimal when a specific performance metric is considered. On the other hand, structured approaches (for instance, a spanning tree) may optimize a given target performance metric but are highly fragile. In fact, the cost for maintaining structures with strong constraints may easily become prohibitive in highly dynamic networks. This chapter discusses different techniques that aim at combining the advantages of unstructured and structured networks. Namely we focus on two distinct approaches, one based on optimizing the overlay and another based on optimizing the gossip mechanism itself. © 2010 Springer Science+Business Media, LLC.