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Raft Consensus Algorithm: an Effective Substitute for Paxos in High Throughput P2P-based Systems

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arxiv 1911.01231 v1 pith:ODJHIOWA submitted 2019-11-04 cs.DC cs.DB

classification cs.DCcs.DB
keywords computingcentralcollisionconsensushighleaderproblemsystems
verification ladder T0 review T1 audit T2 compute T3 formal

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One of the significant problem in peer-to-peer databases is collision problem. These databases do not rely on a central leader that is a reason to increase scalability and fault tolerance. Utilizing these systems in high throughput computing cause more flexibility in computing system and meanwhile solve the problems in most of the computing systems which are depend on a central nodes. There are limited researches in this scope and they seem are not suitable for using in a large scale. In this paper, we used Cassandra which is a distributed database based on peer-to-peer network as a high throughput computing system. Cassandra uses Paxos to elect central leader by default that causes collision problem. Among existent consensus algorithms Raft separates the key elements of consensus, such as leader election, so enforces a stronger degree of coherency to reduce the number of states that must be considered, such as collision.

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  1. Implementing Decentralized Per-Partition Automatic Failover in Azure Cosmos DB

    cs.DB 2025-05 conditional novelty 6.0 of 10

    Cosmos DB introduces per-partition automatic geo-failover driven by a CAS Paxos-backed Failover Manager state machine, restoring write availability in under two minutes in tests.

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