Cloud-Based Collaborative Local-First Software

Detta är en Master-uppsats från Umeå universitet/Institutionen för datavetenskap

Sammanfattning: Local-first software has the potential to offer users a great experience by combining the best aspects of traditional applications with cloud-based applications. However, not much has been documented regarding developing backends for local-first software, particularly one that is scalable while still supporting end-to-end encryption. This thesis presents a backend architecture that was then implemented and evaluated. The implementation was shown to be scalable and was able to maintain an estimated end-to-end latency of around 30-50ms as the number of simulated clients increased. The architecture supports end-to-end encryption to offer user privacy and to ensure that neither cloud nor service providers can access user data. Furthermore, by occasionally performing snapshots the encryption overhead was shown to be manageable compared to the raw data, at around 18.2% in the best case and 118.9% when using data from automerge-perf, a standard benchmark. Lastly, the processing times were shown to be upwards of 50 times faster when using snapshots compared to handling individual changes.

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