A fleet of connected vehicles easily produces many gigabytes of data per hour, making centralized (off-board) data processing impractical. In addition, there is the issue of distributing tasks to on-board units in vehicles and processing them efficiently. Our solution to this problem is OODIDA (On-board/Off-board Distributed Data Analytics), which is a platform that tackles both task distribution to connected vehicles as well as concurrent execution of tasks on arbitrary subsets of edge clients. Its message-passing infrastructure has been implemented in Erlang/OTP, while the end points use a language-independent JSON interface. Computations can be carried out in arbitrary programming languages. The message-passing infrastructure of OODIDA is highly scalable, facilitating the execution of large numbers of concurrent tasks.

翻译：连通车辆车队很容易产生每小时多千兆字节的数据,使中央(离机)数据处理不切实际;此外,还存在将车辆的任务分配给机上单位并高效处理车辆的问题;我们解决这一问题的办法是OODIDA(在机上/离机上分发数据分析器),这是一个平台,既处理向连通车辆的任务分配,又同时执行对边端客户的任意分组的任务;其信息传递基础设施已在Erlang/OTP实施,而终点则使用依赖语言的JSON界面;可任意用程序语言进行计算;OODIDA的信息传递基础设施非常可扩展,便于执行大量同时的任务。