Abstract: Paxos is a well-known distributed algorithm that provides strong consistency. However, the original Paxos has several shortcomings, including those of slow elections, redundant communications and excessive traffic of the coordinator node. In order to tackle the above dificiencies,the design of advanced edition of Paxos(Adv Paxos) was proposed, which is a new distributed consensus algorithm that is derived from Basic Paxos. This paper analyzes the behavior of each character of the original algotithm during each of its phases.  By optimizing the behavior of the proposer and acceptor, a series of behavioral optimization measures was proposed, which included distance related waiting mechanisms, optimization of the number of proposals, self-learning and a reduction in broadcast communications. Through theoretical analysis and experimentation, it is demonstrated that the new algorithm has a lower probability of livelock without a reduction in reliability, faster agreement reaching speeds, lower communication costs among server clusters and higher percentage of successful proposals.

Key words: consensus, Paxos, behavior optimizing, performance