Large-scale behavior of end-to-end epidemic message loss recovery

Abstract

An important class of large-scale distributed applications is insensitive to small inconsistencies among participants, as long as these events are temporary and not frequent. An efficient way for propagating information to participants in such cases is referred to as epidemic protocols. Epidemic protocols are simple, scale well and robust again common failures, and provide eventual consistency as well. They combine benefits of efficiency in hierarchical data dissemination with robustness in flooding protocols. These communication mechanisms have been mainly used for resolving inconsistencies in distributed database updates, failure detection, message loss recovery in multicast communication, network news distribution, group membership management, scalable system management, and resource discovery. In this paper, we focus on an end-to-end epidemic loss recovery mechanism for multicasting and give our simulation results discussing the performance of the approach in large-scale network settings.