Model checking a decentralized storage deduplication protocol

Abstract

Deduplication of live storage volumes in a cloud computing environment is better done by post-processing: by delaying discovery and removal of duplicate data after I/O requests have been concluded, impact in latency can be minimized. When compared to traditional deduplication in backup systems, which can be done in-line and in a centralized fashion, distribution and concurrency lead to increased complexity. This paper outlines a deduplication algorithm for a typical cloud infrastructure with a common storage pool and summarizes how model-checking with the TLA+ toolset was used to uncover and correct some subtle concurrency issues.