Abstract: Real-time video streaming traffic and related applications have witnessed significant growth in recent years. However, this has been accompanied by some challenging issues, predominantly resource utilization. IP multicasting, as a solution to this problem, suffers from many problems. Using scalable video coding could not gain wide adoption in the industry, due to reduced compression efficiency and additional computational complexity. The emerging software-defined networking (SDN)and network function virtualization (NFV) paradigms enable re-searchers to cope with IP multicasting issues in novel ways. In this paper, by leveraging the SDN and NFV concepts, we introduce a cost-aware approach to provide advanced video coding (AVC)-based real-time video streaming services in the network. In this study, we use two types of virtualized network functions (VNFs): virtual reverse proxy (VRP) and virtual transcoder (VTF)functions. At the edge of the network, VRPs are responsible for collecting clients’ requests and sending them to an SDN controller. Then, executing a mixed-integer linear program (MILP) determines an optimal multicast tree from an appropriate set of video source servers to the optimal group of transcoders. The desired video is sent over the multicast tree. The VTFs transcode the received video segments and stream to the requested VRPs over unicast paths. To mitigate the time complexity of the proposed MILPmodel, we propose a heuristic algorithm that determines a near-optimal solution in a reasonable amount of time. Using theMiniNet emulator, we evaluate the proposed approach and show it achieves better performance in terms of cost and resource utilization in comparison with traditional multicast and unicast approaches.

Authors: Alireza Erfanian, Farzad Tashtarian, Reza Farahani, Christian Timmerer, Hermann Hellwagner

IEEE Conference on Network Softwarization 29 June-3 July 2020 // Ghent, Belgium http://netsoft2020.netsoft-ieee.org

Keywords—Dynamic Adaptive Streaming over HTTP (DASH), Real-time Video Streaming, Software Defined Networking (SDN), Video Transcoding, Network Function Virtualization (NFV).

Natalia Sokolova

The 1-page abstract “Pixel-Based Iris and Pupil Segmentation in Cataract Surgery Videos Using Mask R-CNN” was accepted at the workshop “Deep Learning for Biomedical Image Reconstruction” of the International Symposium on Biomedical Imaging that will take place in Iowa-City, Iowa, USA, 3-7 April.

Authors:
Natalia Sokolova, Mario Taschwer, Klaus Schoeffmann

Acknowledment:
This work was funded by the FWF Austrian Science Fund under grant P 31486-N31

The first review of the ASPIDE project took place on 25.02.2020 in the premises of the European Commission in Luxemburg. During the project review, a live demo of the platform for supporting extreme scale applications was presented and future research and developing activities were discussed with the reviewers.

Aspide-Review-2020

Aspide Review 2020

ARTICONF: EU first review

ARTICONF: EU first review

The ITEC team participated in the HiPeac 2020 International Workshop on Exascale programing models for extreme data with a presentation with title “Monitoring data collection and mining for Exascale systems”. The ITEC team also attended the collocated ASPIDE meeting and actively participated in the decision of the next research activities in the project.

Dragi Kimovski

Title of the talk: Mobility-Aware Scheduling of Extreme Data Workflows across the Computing Continuum

Abstract: The appearance of the Fog/Edge computing paradigm, as an emanation of the computing continuum closer to the edge of the network, unravels important opportunities for execution of complex business and scientific workflows near the data sources. The main characteristics of these workflows are (i) their distributed nature, (ii) the vast amount of data (in the order of petabytes) they generate and (iii) the strict latency requirements. Current workflow management approaches rely exclusively on the Cloud Data Centers, which due to their geographical distance in relation to the data sources, could negatively influence the latency and cause violation of workflow requirements. It is therefore essential to research novel concepts for partial offloading of complex workflows closer to where the data is generated, thus reducing the communication latency and the need for frequent data transfers.

In this talk we will explore the  potential  of  the computing continuum  for  scheduling and partial offloading  of  complex  workflows  with  strict  response time requirements and expose the resource provisioning challenges related to the heterogeneity and mobility of the Fog/Edge environment. Consequently, we will discuss a novel mobility-aware Pareto-based approach for task offloading across the continuum, which considers three optimization objectives, namely response time, reliability, and financial cost. Besides, the approach introduces a Markov model to perform a single-step predictive analysis on the mobility of the Fog/Edge devices, thus constraining the task offloading optimization problem to devices that do not frequently move (roam) within the computing continuum. As a conclusion to the talk, we will discuss the efficiency of the presented approach, based on both a simulated and a real-world testbed environment tailored for a set real-world biomedical, meteorological and astronomy workflows.

IWCoCo 2020 in Bologna