CausalMesh: A Formally Verified Causally Consistent Distributed Cache with Support for Client Migration
Haoran Zhang, Zihao Zhang, Shuai Mu, Sebastian Angel, Vincent Liu

TL;DR
CausalMesh is a formally verified distributed cache system that ensures causally consistent data access across migrating clients, improving correctness and performance in cloud applications.
Contribution
It introduces CausalMesh, the first causally consistent cache supporting migration, abort-free operations, and formal correctness verification.
Findings
Lower latency and higher throughput than existing systems
Supports causally consistent read/write operations during client migration
Formally verified correctness in Dafny
Abstract
Cloud applications often insert a caching lay\-er in front of a database in order to reduce I/O latency and improve throughput. One complication occurs when a client fetches some data from one cache node, then migrates to another (e.g., due to failures, load balancing, or client mobility), where it fetches the remaining data. If the data in the cache nodes is inconsistent, the client could observe states that undermine the application's correctness. One example of a situation where this is common is stateful serverless workflows, which consist of multiple serverless functions that access state in a remote database. In serverless, functions in the same workflow may be scheduled to different nodes with different caches, resulting in the migration pattern described above -- the same client (the workflow) reads some data from one cache and other data from another. To address this issue,…
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