A dynamic task scheduler to execute job chains in a fault-tolerant way
This project provide an easy to deploy service oriented task-scheduling architecture capable to achieve a fault-tolerant job execution on dynamics networks.
The system use:
- A robust Job scheduler: Quartz Enterprise scheduler (for more info see http://www.quartz-scheduler.org)
- A framework to build reliable dynamic distributed systems: Apache River framework (for more info see http://river.apache.org)
PyMW is a Python module for parallel master-worker computing in a variety of environments. With the PyMW module, users can write a single program that scales from multicore machines to global computing platforms.
...It focuses on distributed computing and data gathering in Internet environment. Intended for smaller projects requiring couple hundreds of computers gathered together for a master-worker like jobs.
RAFT-Net is a Fault Tolerant Parallel Distributed Framework.
Using a Master-Worker scheme, the framework transparently
distributes workunits to workers (drones). These workers can join and
leave and as such, the network is very flexible. A modified