Enhancing Locality via Caching in the GMU Protocol

GMU is a recently proposed genuine partial replication protocol for transactional systems that relies on an innovative, fully-decentralized multiversioning scheme to maximize efficiency and scalability. In this paper we tackle one of the key issues that affect the efficiency of GMU-based applications: enhancing their data locality, i.e. the ability to serve transactional reads locally, avoiding remote inter-node communication. To this end we introduce a lightweight caching mechanism that allows for safely accessing asynchronously replicated copies of remote data items while preserving GMU's original consistency criterion and its scalability. We assess the efficiency and effectiveness of the presented solution by means of an extensive experimental analysis, evaluating deployments on large scale public and private cloud infrastructures, and using well known benchmarks for transactional platforms. The results show striking speedups of up to 14 times in read dominated workloads, and a reduction of the network bandwidth by up to one order of magnitude.