A Scalable Sequence Encoding For Collaborative Editing

Distributed real-time editors made real-time editing easy for millions of users. However, main stream editors rely on Cloud services to mediate sessions raising privacy and scalability issues. Decentralized editors tackle privacy issues, but scalability issues remain. We aim to build a decentralized editor that allows real-time editing anytime, anywhere, whatever is the number of participants. In this study, we propose an approach based on a massively replicated sequence data structure that represents the shared document. We establish an original trade-off on communication, time, and space complexity to maintain this sequence over a network of browsers. We prove a sublinear upper bound on communication complexity while preserving an affordable time and space complexity. To validate this trade-off, we built a full working editor and measured its performance on large-scale experiments involving up till 600 participants. As expected, the results show a traffic increasing as O((logI)2lnR) where I is the number of insertions in the document, and R the number of participants.