3rd PrEstoCloud Press release: Cloud-based PrEstoCloud pilot manages huge data streams from video surveillance systems

Darmstadt, Germany, August 23, 2018 – PrEstoCloud (http://prestocloud-project.eu) is a research project funded by the European Commission with the goal of developing a dynamic and distributed software architecture platform that manages cloud and fog resources proactively, while utilizing edge resources for efficient real-time big data processing. Three pilot projects in different domains will demonstrate the power of PrEstoCloud’s new approach: wide-area video and audio surveillance, logistics, and mobile journalism. Based on an innovative architecture, the smart video and audio surveillance system combines extreme edge, fog and cloud computing. The surveillance pilot is now ready for demonstration.

The dramatic rise in IoT devices that transmit vast amounts of data has given way to a steadily expanding market of devices that transmit video for surveillance purposes. Current surveillance systems produce massive amounts of video content while operating 24 hours a day, seven days a week. Huge video data streams have to be processed quickly in order to summarize events occurring during a specific time frame at a particular location. Concepts like fog computing—based on data processing closer to where the data is produced—will reduce the need for extensive bandwidth and remote processing power of existing cloud-based solutions.
The wide-area video and audio surveillance pilot project ensures that video and audio streams produced by cameras are processed at the extreme edge of a network. Thanks to small computational devices located next to cameras, unnecessary network exchange and—in the case of wide-area video and audio surveillance with many cameras—significant overhead is avoided. When sufficient edge resources are not available, processing can be offloaded to other computational devices—either at the same location (e.g. a server) or in a private or public cloud. This offers the considerable benefit of reduced bandwidth, given that 1,000 cameras can produce up to 125 TB of data in one hour of video stream. Another key benefit is the lowered risk of data leaks and compromised data integrity in the event of an attack.

The research consortium has created the components and the framework to enable deployment of distributed processing applications on both cloud and edge devices. Furthermore, the PrEstoCloud framework is built on top of an intercloud virtualization layer and mesh network that can be used to connect the deployed applications. It fully supports fog deployment. This pilot shows how PrEstoCloud enables applications to scale in a dynamic fashion while at the same time cutting costs and bandwidth.

The consortium unites a total of eleven partner organizations from industry and research, working on the efficient exploitation of infrastructural resources from mobile edge devices to the clouds. The aim is to improve cloud infrastructures’ capabilities for handling big data applications. The project was officially launched on January 1, 2017 and will run for three years. ADITESS LTD (www.aditess.com) is technical partner of the consortium.