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Newsletter December 2019 - Issue 5

Message from the Coordinator

Hello everybody,

Welcome to the last issue of the PrEstoCloud Newsletter. PrEstoCloud is nearing completion. Including the preparation phase for this project, we jointly developed and shaped our ideas and innovations on the topic of "Cloud Computing" for almost four years. During this period, we developed an architecture, that manages cloud and fog resources proactively, enabling to reach the extreme edge of the network. Also, three pilot projects in different domains demonstrates the power of PrEstoCloud's new approach. In addition, we have produced an impressive number of publications and appearances at conferences, giving new impetus to the academic world. Looking back today, we can see that the selection of partners, but especially the structuring of our project of nine work packages, including the three use cases, was chosen purposefully. Numerous innovations were initiated and point to a promising exploitation of the project results. I wish us all every success in this respect.

Facing the end of the official project phase I would like to take the opportunity to thank all consortium partners for their inspiring and effective cooperation. In numerous face-to-face meetings and working groups, all have contributed their respective technological experiences and have further developed them into a successful dialogue between science and industry. I would also like to thank especially the Project Officer Luis C. Busquets Pérez, who facilitated the administrative handling of our project and all involved members and responsibles of the European Commission in supporting us during the whole project phase.

I wish you happy holidays and a wonderful 2020. Enjoy reading!

With best regards,

Dirk Mayer, Software AG
Project Coordinator

PrEstoCloud Use Cases

PrEstoCloud mainly focussed on three industry domains that have been covered by PrEstoCloud pilots. They demonstrate the power of PrEstoCloud's new approach:

Logistics Pilot

The CVS logistics application is capable of tracking their vehicles movements, the geographic locations where driving dynamics (e.g. sudden acceleration, hard braking, aggressive right turn and aggressive left turn) happened and what types of driving dynamics occurred during the trips. The CVS logistics centre is now able to profile their drivers’ behaviour and associated statistics. Moreover, the CVS logistics application implemented by the PrEstoCloud project knows if any driver is dangerously manoeuvring at the moment on situations when many driving dynamics are currently happening.

Through the CVS logistics application implemented in the PrEstoCloud solution, stakeholders such as operators of the logistics centre, vehicles owners, drivers and insurance companies can track, maintain, optimise, and manage the telematics data and logistical assets such as their fleet of vehicles. CVS takes advantage of the following benefits:
  • Increasing fleet safety which is an objective for the CVS Mobile. For example, telematics data is useful for evaluating and hence correcting driver behaviour that insurance companies hopefully begin to offer discounts for the CVS Mobile.
  • Telematics data allows the CVS Mobile to optimise maintenance schedules since developing custom maintenance schedules for each vehicle is necessary to identify when and where performance issues arise in a fleet vehicle. For example, the CVS Mobile can be able to determine when a fleet vehicle may need an oil change, new braking pads or a filter swap, and hence the CVS fleets will be capable of paying for maintenance more efficiently.
  • Minimising infrastructure costs through technologies by which services and data can be efficiently provisioned, monitored and migrated across federated cloud, fog and edge resources.

Surveillance Pilot

The surveillance systems, that capture video and audio in enterprise facilities and public places, produce massive amounts of data while operating in a 24/7 mode. There is an increasing need to process, on the fly, such huge video and audio data streams to enable a quick summary of “interesting” events that are happening during a specified time frame at a particular 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 builds on top of a distributed computing paradigm and is ideal for smart surveillance systems that can utilize resources at cloud, fog and edge. The surveillance use cases 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 the PrEstoCloud Project, we enabled a novel and adaptive architecture that built on top of a distributed computing paradigm which is ideal for smart surveillance systems that uses resources at cloud, fog and edge.

  • Video analysis at the edge of the network is part of new concepts for cloud computing and increases company profile.
  • Cost savings by deploying efficient processing at the edge especially for video.
  • Cost efficiency- use of legacy Hardware (HW)
  • Unmanned Aerial Vehicle (UAV) integration under the same framework
  • More efficient data analysis at the edge providing a distributing surveillance system
  • Only analytics outputs and some functions run on cloud
  • Better utilization of resources at the edge of the network
  • Higher security features
  • Less storage in the cloud
  • Less data transfer to the cloud
  • Higher trust and privacy having less processing in the cloud

Mobile Journalism Pilot

LiveU and N.Amram Technologies have developed a product for Mobile Journalism users. Nowadays, when life is very dynamic, anyone can become an eyewitness of some remarkable event. At the same time, a high level of e-communication between people via communication tools encourage everyone to become a newsmaker. This trend creates new opportunities for news companies in optimization their operation by using Mobile Journalism. The application developed by LiveU and NAM allows news companies, professionals and volunteers to work together on news making: to analyse live video streams by using video analytics, communicate in private virtual rooms, exchange video feeds. With PrEstoCloud platform, all these services are optimised in terms of hardware resources and costs which allows news companies to minimize their expenses and at the same time keep the high quality of news feeds.

PrEstoCloud Architecture and Technologies

Fog Context Analytics Component

Fog computing environments are unstable and diverse. Edge devices with different hardware and software configuration have different processing capabilities and performance. Factors such as the available RAM, the type of memory chips, the number of CPU cores, frequency, type and generation, the current battery level (when the device lowers CPU clock frequency in order to lower energy consumption) or the speed of storage devices (HD, SSD, Flash) may affect the QoS (Quality of Service, e.g. total execution time) of application and services in different ways. Considering the aforementioned characteristics of fog computing, with the term context we refer to any information (such as CPU, memory or utilization, network type and traffic, battery state, software and hardware configuration, etc.) that can help to infer conclusions about current and future state of fog devices.

A clear and accurate classification of context is helpful to uncover, understand, manipulate and sort out a variety of sensor-generated data to uncover useful information about the status of a computing resource and help DevOps make infrastructure management decisions. Many machine learning methods and mathematical representations of fog infrastructures have been used to convert low-level sensor data into higher-level context, which can facilitate decision- making. Indicative methods used for context classification include Hidden Markov Models, Markov Chains, Bayesian Networks, Nearest Neighbor, Time Series, Threshold based Learning and Gaussian Mixture Models.

ICCS has analysed key methods of context classification and prediction and the application of these methods to facilitate fog infrastructure management. In the context of PrEstoCloud, ICCS has developed a Fog Context Analytics component, which can support infrastructure operators in case where there is an increased demand for management automation, robustness and overall management complexity reduction to achieve good quality of service and serve demands of different devices and applications. The software component is available at GitLab.

Mobile Offload Processing

Mobile based real-time processing network based on cloud-edge communication layer was developed and deployed by JSI for general PrEstoCloud platform and supporting variety of situations including all three use cases of the project. Video is available here.

PrEstoCloud on Tour

PrEstoCloud Webinars
On November 29, and September 4 the PrEstoCloud Webinars took place. Participants were informed about PrEstoCloud project in general, the microservices architecture, proposed key influencing auto-scaling factors, and the empirical evaluation. Of course, there was an opportunity for interaction and discussion.

Plenary Meeting in Nice
The plenary meeting held in Nice on November 5-8, 2019 was organized by Activeeon. The last meeting focused on the results of the work packages as well as on the milestones achieved. In addition, the individual exploitation plans were discussed. With a look into the future, the review in February and the PrEstoCloud life after the end were looked at.

View the gallery

PrEstoCloud Meeting in Athens
The plenary meeting held in Athens on September 12-13, 2019 was organized by UBITECH. In the course of the previous face-to-face meeting in Niŝ, this meeting was mostly focused on discussion of validation and evaluation of the PrEstoCloud platform by the use cases. Each use case owner (ADITESS, CVS, and LiveU/NAM) presented tests, which will be carried out according to validation and evaluation plan, to the platform developers. The discussion followed each presentation helped both use case teams and the platform developers to prepare better to the final stage of the project.

View the gallery

International Workshop on Autonomic High Performance Computing (AHPC 2019)
The PrEstoCloud project team work benefited from the discussion within the 2019 International Workshop on Autonomic High Performance Computing (AHPC 2019) organized and chaired by Prof. Françoise Baude (CNRS/I3S). The workshop AHPC 2019 was co-located with the 2019 International Conference on High Performance Computing and Simulation (HPCS 2019), at the Grand Hotel Malahide in Dublin, Ireland, on June 15-19, 2019. The workshop focused on autonomic computing with an emphasis on self-manageable systems that exhibit self-configuration, self-healing, self-protection, self-optimization, and/or self-monitoring, which is ubiquitous in the world of distributed applications, such as embedded/IoT devices, cloud, and big data applications, such as targeted by the PrEstoCloud project.

PrEstoCloud Meeting in Niŝ
The plenary meeting held in Niŝ on May 22-23, 2019 was organized by Nissatech. The main focus of the meeting was on the use cases, their presentation, live demonstration via the PrEstoCloud deployment GUI, and discussion of the current progress. Each use case team presented a technical architecture of the use case and its components as well as data sources to be connected to the PrEstoCloud platform. Special attention was paid to validation and verification general approach, current status and further steps. Another important part of the plenary meeting in Niŝ was a hackathon. Hackathons have already become the traditional activity at PrEstoCloud plenary meetings since they help in better interaction between development teams of different organizations in the PrEstoCloud consortium.

View the gallery

Telematics Conference CEEurope in Prague
Telematics Conference CEEurope in Prague hosted PrEstoCloud project the second time. On 26th September, Demo of current CVS edge to cloud technology platform solution impressed many participants including commercial telematics ones. It showed a new wave and opportunities for further development within fleet management operations, driver’s profiling not to mention connecting professionals with approach to upgraded insurance concept possibilities.

PrEstoCloud at SIGKDD Conference in Anchorage
SIGKDD project showcase track on August 4-8 in Anchorage, Alaska brought together a diverse community of researchers in machine learning and data analytics with the aim of promoting innovation and stare-of-the-art research in presented areas. JSI and CVS mobile introduced poster and orally presented accepted paper on Efficient Real-Time Big Data Processing at the Edge of the Network.

Upcoming Events

Hannover Messe 2020
PrEstocloud belongs to one of the research projects being shown at Hannover Messe 2020 at the booth of Software AG. From 20 - 24 April 2020, Software AG's research manager will be there to share the research findings to visitors from the manufacturing industries and the energy sector.

Dissemination Material

In the final phase of the project, many publications emerged from the teamwork. Here you will find a list of new dissemination activities: Scientific papers from the last project year:
Scientific papers from the last project year
  • Key influencing factors of the Kubernetes auto-scaler for computing-intensive microservice-native cloud-based applications. Advances in Engineering Software 140, Elsevier, 2019. Get the paper!
    Taherizadeh, Salman; Grobelnik, Marko
  • SWITCH workbench: A novel approach for the development and deployment of time-critical microservice-based cloud-native applications. Future generation computer systems 99, Elsevier, 2019. Get the paper!
    Stefanic, Polona; Cigale, Matej; Jones, Andrew C.; Knight, Louise; Taylor, Ian; Istrate, Cristiana; Suciu, George; Ulisses, Alexandre; Stankovski, Vlado; Taherizadeh, Salman; et al.
  • Dynamic multi-level auto-scaling rules for containerized applications. The computer journal 62(2), Oxford University Press, 2019. Get the paper!
    Taherizadeh, Salman; Stankovski, Vlado
  • Measuring the Amazon Web Services (AWS) WAN Infrastructure at CoRes 2019 (Rencontres Francophones sur la Conception de Protocoles, l'Evaluation de Performance, et l'Expérimentation des Réseaux de Communication), 2019. Get the paper!
    Jacquemart, Quentin; Vitali, Alessandro; Urvoy-Keller, Guillaume
  • nferring the Deployment of Top Domains over Public Clouds using DNS Data at the 3rd Network Traffic Measurement and Analysis Conference (TMA 2019). Get the paper!
    Jacquemart, Quentin; Pigout, Clément; Urvoy-Keller, Guillaume
  • Efficient Real-Time Big Data Processing at the Edge of the Network – The PrEstoCloud project. KDD 2019 Project Showcase Track (KDD 2019), ACM, Alaska, United States, 2019. Get the paper!
    Taherizadeh, Salman; Novak, Blaz; Vagaja, Sebastjan; Komatar, Marija; Grobelnik, Marko

A clear overview of the project and the use cases can be found in the videos.
Blog Posts
On the PrEstoCloud Blog you will find some topics and questions that research partners have dealt with in the last three years.

Meet our Project Team

The multinational research consortium consists of very experienced researchers and technology developers, who have already provided parts of the system that will be used as a basis for developing the PrEstoCloud platform. The consortium unites a total of eleven partner organizations from industry and research. Software AG has been entrusted with the leadership of the consortium

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ijs logo liveu logo amram-tech logo nissatech logo Ubitech logo

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January 2017 - December 2019
Reference 732339 • Volume 4.2 mio. Euro • Partners 11