pythonc++juliacross-platforminterprocess

Cleanest method of inter-program communication on separate devices


I need to settle on a method of communication between multiple programs spread out over multiple machines. The data itself is fairly straight forwards, comprising of variable length vectors with some meta-data descriptors.

Each program "type" will send data to 1 other program type, and expects to see a reply from it.

The number of connections a given program has is variable over time, and programs can be added or removed at any moment.

Programs may be distributed across several processors, which may use different operating systems, or could be microprocessors.

Example program structure

I have not had to really contend with such a inter-communication puzzle before and am unsure of what the cleanest approach would be. I've heard that ROS might be useful, but that it may not be suitable for Windows environments and has a steep learning curve. I can imagine creating a database between the nodes which would act as a kind of blackboard, but this feels like it may be very inefficient. If using sockets would resolve efficiencies, then how would the connections be managed / maintained?

My main development environment at the moment is Julia, but I can port the data over to C++ or Python without too much discomfort.

I am open to ideas and learning new things, but I can't figure out which path to take. Any nuggets of wisdom would be greatly appreciated.


As requested in a comment, here is some additional information:


Solution

  • Perhaps taking a look at something well established (and therefore should be able to hook up to whichever language/s you end up using) like Redis or RabbitMQ would be wise seeing as you'll need to be able to communicate with a number of different devices over a network. Either way having some form of central hub that handles communication among the other devices would be advisable.