M-Lock: Accelerating Distributed Transactions on Key-Value Stores through Dynamic Lock Localization

Scalable distributed data-stores are increasingly used for storing large datasets in diverse applications. The need for transactional support in these applications has motivated several recent efforts. A common theme underlying these efforts is the creation of disjoint groups of objects (entity-groups) on which efficient local transactional support is provided using multi-version concurrency control. A lock-based protocol is used to support distributed transactions across entity-groups. A significant drawback of this scheme is that the latency of distributed transactions increases with the number of entity-groups it operates on. This is due to the commit overhead of local transactions, and network overhead due to distributed locks. We address this problem using lock-localization -- locks for distributed objects are dynamically migrated and placed in distinct entity-groups in the same datastore. This reduces the overhead of multiple local transactions while acquiring locks. Application-oriented clustering of locks in these new entity-groups leads to a decrease in network overhead. Separating locks from data in this manner, however, affects the latency of local transactions. To account for this, we propose protocols and policies for selective, adaptive, and dynamic migration of locks. Using TPC-C benchmark, we provide detailed evaluation of the system.