A look to the old-world_sky: EU-funded dependability cloud computing research
ACM SIGOPS Operating Systems Review
ACM SIGOPS Operating Systems Review
Elastic, scalable and self-tuning data replication in the cloud-TM platform
Proceedings of the 1st European Workshop on Dependable Cloud Computing
SCORe: a scalable one-copy serializable partial replication protocol
Proceedings of the 13th International Middleware Conference
Hyflow2: a high performance distributed transactional memory framework in scala
Proceedings of the 2013 International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools
A framework for high performance simulation of transactional data grid platforms
Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques
Enhancing concurrency in distributed transactional memory through commutativity
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
On the scalability of snapshot isolation
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
Scalable service-oriented replication with flexible consistency guarantee in the cloud
Information Sciences: an International Journal
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In this article we introduce GMU, a genuine partial replication protocol for transactional systems, which exploits an innovative, highly scalable, distributed multiversioning scheme. Unlike existing multiversion-based solutions, GMU does not rely on a global logical clock, which represents a contention point and can limit system scalability. Also, GMU never aborts read-only transactions and spares them from distributed validation schemes. This makes GMU particularly efficient in presence of read-intensive workloads, as typical of a wide range of real-world applications. GMU guarantees the Extended Update Serializability (EUS) isolation level. This consistency criterion is particularly attractive as it is sufficiently strong to ensure correctness even for very demanding applications (such as TPC-C), but is also weak enough to allow efficient and scalable implementations, such as GMU. Further, unlike several relaxed consistency models proposed in literature, EUS has simple and intuitive semantics, thus being an attractive, scalable consistency model for ordinary programmers. We integrated the GMU protocol in a popular open source in-memory transactional data grid, namely Infinispan. On the basis of a large scale experimental study performed on heterogeneous experimental platforms and using industry standard benchmarks (namely TPC-C and YCSB), we show that GMU achieves linear scalability and that it introduces negligible overheads (less than 10%), with respect to solutions ensuring non-serializable semantics, in a wide range of workloads.