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Chapter 8 Conclusion The most useful piece of learning for the uses of life is to unlearn what is untrue. Antisthenes Paxos has been synonymous with distributed consensus for over two decades. As such, it has been extensively researched, taught and deployed in production. This thesis sought to reconsider how we approach consensus in distributed systems and challenge the widely held belief that the Paxos algorithm is an optimal solution to consensus. 8.1 Motivation In section 1.3, we outline limitations of Paxos. Aside from the algorithm’s subtlety and underspecification, decisions are slow as two round trips to the majority of acceptors is needed for each decision. This approach leads to a high message overhead, which increases linearly with the number of acceptors and is limited in scalability as each additional acceptor increases the size of the majority and thus decreases performance. Paxos relies on synchrony to avoid duelling between proposers and also relies on the majority of acceptors being live to make progress. Paxos tightly couples the number of participants, availability in the face of failures and steady state performance. Paxos offers a one-size-fits-all solution to distributed consensus which is highly symmetric, following a single set execution path, regardless of the state of the system. Paxos guarantees that a proposer will terminate in two rounds given its liveness conditions, namely synchrony, exactly one proposer is live and at least a majority of acceptors are live. If these conditions are not satisfied, Paxos provides little in the way of progress guarantees. If stronger conditions are satisfied then Paxos still requires two rounds with majority agreement to make progress. 141PDF Image | Distributed consensus
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