Formal analysis techniques for gossiping protocols

We give a survey of formal verification techniques that can be used to corroborate existing experimental results for gossiping protocols in a rigorous manner. We present properties of interest for gossiping protocols and discuss how various formal evaluation techniques can be employed to predict them

The mutable consensus protocol

In this paper we propose the mutable consensus protocol, a pragmatic and theoretically appealing approach to enhance the performance of distributed consensus. First, an apparently inefficient protocol is developed using the simple stubborn channel abstraction for unreliable message passing. Then, performance is improved by introducing judiciously chosen finite delays in the implementation of channels. Although this does not compromise correctness, which rests on an asynchronous system model, it makes it likely that the transmission of some messages is avoided and thus the message exchange pattern at the network level changes noticeably. By choosing different delays in the underlying stubborn channels, the mutable consensus protocol can actually be made to resemble several different protocols. Besides presenting the mutable consensus protocol and four different mutations, we evaluate in detail the particularly interesting permutation gossip mutation, which allows the protocol to scale gracefully to a large number of processes by balancing the number of messages to be handled by each process with the number of communication steps required to decide. The evaluation is performed using a realistic simulation model which accurately reproduces resource consumption in real systems.FCT , project STRONGREP (POSI/CHS/41285/2001)

Process membership in asynchronous environments

The development of reliable distributed software is simplified by the ability to assume a fail-stop failure model. The emulation of such a model in an asynchronous distributed environment is discussed. The solution proposed, called Strong-GMP, can be supported through a highly efficient protocol, and was implemented as part of a distributed systems software project at Cornell University. The precise definition of the problem, the protocol, correctness proofs, and an analysis of costs are addressed