Publication | Open Access
Logoot: A Scalable Optimistic Replication Algorithm for Collaborative Editing on P2P Networks
141
Citations
22
References
2009
Year
Unknown Venue
Cluster ComputingMassive CollaborationEngineeringCollaborative Information RetrievalCollaborative EditingSemantic WebData ConsistencyInformation RetrievalData ScienceP2p NetworksMassive CollaborativeLogoot ApproachData IntegrationData ManagementCollaborative ComputingWeb-based CollaborationReal-time CollaborationSocial Network AnalysisComputer ScienceData ReplicationNetwork ScienceDistributed CollaborationCloud ComputingPeer-to-peer DatabaseTrusted P2pDistributed Transaction
Massive collaborative editing becomes a reality through leading projects such as Wikipedia. This massive collaboration is currently supported with a costly central service. In order to avoid such costs, we aim to provide a peer-to-peer collaborative editing system. Existing approaches to build distributed collaborative editing systems either do not scale in terms of number of users or in terms of number of edits. We present the Logoot approach that scales in these both dimensions while ensuring causality, consistency and intention preservation criteria. We evaluate the Logoot approach and compare it to others using a corpus of all the edits applied on a set of the most edited and the biggest pages of Wikipedia.
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