Abstract
AbstractA 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 On-board/Off-board Distributed Data Analytics (OODIDA), 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.
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Computational Mechanics
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