The multiprocess communication library (a.k.a MCL) provides software for developing low-latency, message-passing systems. Message-passing is performed using IPv6 multicast. Two key concepts underpin the design philosophy of and use of MCL: the publish-subscribe paradigm and inter-process communication.

To ensure the success and longevity of a software project, it must be extensible and reliable. MCL encourages users to adopt a modular design when developing software projects. By breaking up software into modules of functionality, small portions of code can be independently developed and maintained - increasing flexibility, maintainability and extensibility. To transfer information from one module to another, the publish-subscribe paradigm can be used. This strategy allows event-driven code to be run on many independent processes. Message passing over the publish-subscribe network allows communication to occur transparently within a single computer, across multiple computers and across heterogeneous devices.

MCL was developed at The Intelligent Vehicles and Safety Systems Group at the Australian Centre for Field Robotics (ACFR).

This code supports installation using pip (via setuptools). To install from the git repository:

git clone https://github.com/acfr/mcl
cd mcl
sudo pip install .

To uninstall the package:

pip uninstall mcl

The documentation is hosted online at Read the Docs.

To build a local copy of the HTML Sphinx documentation run:

make docs

The entry point of the documentation can then be found at:

doc/build/html/index.html

• Dr Asher Bender
• Dr James Ward
• Dr Stewart Worrall

If you use this work for academic research please cite the following article:

Bender, A.; Ward, J. R.; Worrall, S.; Moreyra, M.; Konrad, S. G.; Masson, F. & Nebot, E. M., "A Flexible System Architecture for Acquisition and Storage of Naturalistic Driving Data", IEEE Transactions on Intelligent Transportation Systems, 2016, pp. 1-14

BibTeX:

@Article{Bender2016,
  Title     = {A Flexible System Architecture for Acquisition and Storage of Naturalistic Driving Data},
  Author    = {Asher Bender and James R. Ward and Stewart Worrall and Marcelo Moreyra and Santiago Gerling Konrad and Favio Masson and Eduardo M.~Nebot},
  Journal   = {IEEE Transactions on Intelligent Transportation Systems},
  Year      = {2016},
  Number    = {99},
  Pages     = {1-14},
  Volume    = {PP},
  Doi       = {10.1109/TITS.2016.2524523},
  ISSN      = {1524-9050},
}

Redistribution and use of this library, with or without modification, are permitted under the terms of the BSD 3-Clause license. See LICENSE.txt.