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Browsing by Author "Peluso, Sebastiano"

Now showing 1 - 2 of 2
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    Generalized Consensus for Practical Fault-Tolerance
    Garg, Mohit (Virginia Tech, 2018-09-07)
    Despite extensive research on Byzantine Fault Tolerant (BFT) systems, overheads associated with such solutions preclude widespread adoption. Past efforts such as the Cross Fault Tolerance (XFT) model address this problem by making a weaker assumption that a majority of processes are correct and communicate synchronously. Although XPaxos of Liu et al. (using the XFT model) achieves similar performance as Paxos, it does not scale with the number of faults. Also, its reliance on a single leader introduces considerable downtime in case of failures. This thesis presents Elpis, the first multi-leader XFT consensus protocol. By adopting the Generalized Consensus specification from the Crash Fault Tolerance model, we were able to devise a multi-leader protocol that exploits the commutativity property inherent in the commands ordered by the system. Elpis maps accessed objects to non-faulty processes during periods of synchrony. Subsequently, these processes order all commands which access these objects. Experimental evaluation confirms the effectiveness of this approach: Elpis achieves up to 2x speedup over XPaxos and up to 3.5x speedup over state-of-the-art Byzantine Fault-Tolerant Consensus Protocols.
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    Taming the Contention in Consensus-Based Distributed Systems
    Arun, Balaji; Peluso, Sebastiano; Palmieri, Roberto; Losa, Giuliano; Ravindran, Binoy (IEEE, 2021-11-01)
    Contention plays a crucial role in the design of consensus protocols. State-of-the-art solutions optimize their performance for either very low or high contention situations. We propose Caesar, a novel multi-leader Generalized Consensus protocol, most suitable for geographical replication, that is optimized for low-to-moderate contention. With an evaluation study, we show that Caesar outperforms other multi-leader (e.g., EPaxos) and single-leader (e.g., Multi-Paxos) competitors by up to 1.7x and 3.5x, respectively, in the presence of 30 percent conflicting requests, in a geo-replicated setting. Furthermore, we acknowledge that there is no one-size-fits- all consensus solution, especially for all levels of contentious workloads. Thus, we also propose Spectrum, a consensus framework that is able to switch consensus protocols at runtime to enable a dynamic reaction to changes in the workload and deployment characteristics. We show empirically that Spectrum can guarantee high availability even during periods of transition between consensus protocols.