Fujitsu Laboratories has developed a stream processing architecture that can add or change content while processing large volumes of IoT data, without stopping. Called Dracena (Dynamically Reconfigurable Asynchronous Consistent EveNt-processing Architecture), the system is hoped to help in the progression towards autonomous driving which requires the analysis of the vast amounts of information, such as speed and location, generated from vehicles, which can then be presented to drivers.
The stream processing architecture is effective in the high-speed processing of huge volumes of data such as that from autonomous cars but has drawbacks because processing must be temporarily stopped when changing or adding processing content according to additions or improvements to services, leading to delay in the provision of services.
According to Fujitsu, Dracena automatically switches to a newly provided data processing program when a parallelized data processing job has been completed, by separating stream processing into data reception processing and actual data processing so that data reception processing and current data processing are not stopped.
Fujitsu Laboratories is looking to commercialize this technology during fiscal 2018 on the Mobility IoT Platform, offered by Fujitsu Ltd., and extend it to other industry areas.