Concurrent execution is a big challenge for distributed systems programming and cloud computing. Using locks is the most common technique for developing distributed applications that require tight synchronization. Unfortunately, locking is manual, error-prone, and unscalable. To address this issue, we propose a scalable automated locking framework called Maestro. Maestro consists of a master and several workers, which can be dynamically instantiated on demand. Maestro examines the program actions of the workers before deployment and automatically decides which worker actions can be executed locally (without contacting the master) and which actions require synchronization through the master. Maestro has applications in graph processing, real-time enterprise analysis, and web-services domains. By enabling the developers to write code at a higher-level of abstraction (shared-memory), Maestro improves productivity and lowers the cost of entry to cloud computing backend development.
['Murat Demirbas', 'Serafettin Tasci', 'Sandeep S. Kulkarni']
Maestro: A cloud computing framework with automated locking