Supply-Chain management systems deal with massive amounts of data. In today's scenario, with numerous inventories to track, they're unable to work efficiently because 1. they are not fault-tolerant 2. their data is stored on a single database, and 3. they require manual reconfiguration in case of errors. We introduce factoryOS, a distributed and self-organizing planning system that can cope with these challenges. factoryOS is robust to network delays and fault-tolerant, partitions inventory data natively, and works without any manual intervention. Our novel design point is that we're able to guarantee uninterrupted production even with multiple failures. With factoryOS, partition shards are created natively and nodes handle their own processes individually. Our experimental results show that factoryOS can be easily scaled to a large number of nodes and is fault-tolerant to a high degree of failures.
python3.5 -m pip install -r requirements.txtTo spawn multiple processes automatically, run the following commands. Number of types represents the items being produced, while nodes_per_type represents the duplication for the nodes.
python main.py --num_types 5 --nodes_per_type 2 --complexity highTo run a dynamic GUI reflecting the cluster changes, run,
python main.py --num_types 5 --nodes_per_type 2 --complexity high --run_plotter True