EU funded research project delivers real-time, data-intensive applications for cloud, edge and fog computing environments
The PrEstoCloud platform offers Big Data service providers the ability to optimize resource utilization for their client applications and provide an improved client-oriented Quality of Service. PrEstoCloud combines real-time Big Data, mobile processing and Cloud computing research in a unique way and provides an innovative solution for the complex problem of cloud-based, self-adaptive, real-time Big Data processing.
Based on the PrEstoCloud platform the European project team validated the progress and benefits of this new approach within three different use cases: wide-area video and audio surveillance, logistics, and mobile journalism. With the validation of these three pilots from different domains, PrEstoCloud shows the transferability of the architecture and the platform to other possible customer segments seeking for efficient real-time Big Data processing and using IoT within their business processes.
Logistics pilot – Optimizing runtime resource management
Vehicles are in effect moving data sources that generate massive volumes of data resulting in heavy ground station to satellite network traffic. The logistics pilot, developed by CVS Mobile Logistics, analyses the collected sensor data and triggers notifications at run-time in order to monitor drivers’ behavior and identify unexpected driving events, providing optimized runtime resource management across private clouds, public clouds and edge nodes, PrEstoCloud provides cost optimization by improving efficiency in the amount of data collected from the vehicle that will be sent to and stored in the cloud and simultaneously improves performance in terms of response time.
Surveillance pilot – Minimizing Cloud and maintenance fees
The surveillance systems, that capture video and audio in enterprises and public places, produce massive amounts of data 24/7. There is an increasing need to process such huge video and audio data streams in real time to enable a quick summary of “interesting” events that happen during a specified time frame at a location. The smart surveillance application, developed by ADITESS, is a combination of audio/video analytics with visualization detecting security events and informing the appropriate security personnel. A novel and adaptive architecture built on top of a distributed computing environment is ideal for smart surveillance systems that can utilize resources in the cloud, fog and at the edge. This surveillance use case demonstrates how PrEstoCloud can ensure the availability of services, system integrity and real-time detection of illicit activity despite the increased workload, unexpected failure of devices or computational components. Through PrEstoCloud, a robust and reliable surveillance system minimizes cloud and maintenance fees by maximizing the use of the available resources.
Mobile Journalism Pilot – Supporting Mobile Journalism
A high level of e-communication between people via social networks and different communication tools encourages everyone to become a newsmaker. This creates new opportunities for news companies in the optimization their operations by using mobile journalism, including both professionals and volunteers who happened to be eyewitnesses to current events. The Media Use Case Software enables the real time transmission, handling, and analysis of video streams. The software consists of containerized components ready for deployment to the PrEstoCloud platform. The News Room Application allows two categories of users, reporters and producers, to work with live media content as well as to communicate using private ‘rooms’. The MultiMedia Hub enables the collection, handling and distribution of media streams. The Video Analytics System allows recognition of objects (faces) in a video stream produces analytics to help users in handling multiple live media streams available in the News Room Application. The software of the Media Use Case is developed by LiveU and NAM.
High Academic and Technical Achievements
PrEstoCloud delivered substantial research contributions in the field of Cloud Computing and real-time Big Data technologies, which has resulted in numerous papers and articles been published in renowned journals and presented at scientific conferences. The computer science journal “Advances in Engineering Software”, published an article about a set of key factors which should be considered in the development of auto-scaling methods. The research publications also describe different new technical solutions such as Mobile Context Analyzer, which allows the detection and enhancement of context data gathered from devices at the extreme edge of the network. Also, the Situation Detection Mechanism which allows the detection of situations that require infrastructure or application adaptation. A complete list of publications is published on the website.
The PrEstoCloud consortium united a total of eleven partner organizations from industry and research. The EU funded project was officially launched on January 1, 2017 and will end December 31, 2019. Software AG has been entrusted with project coordination of PrEstoCloud.
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