The PhD defense is in progress. @ilyushkin of @LargeResearch and @EEMCS_TUD discusses his work with @RaduProdanAAU. Science at work. pic.twitter.com/ubSZoXRYCR
— Alexandru Iosup (@AIosup) December 19, 2019
High-tech meets history. When thousands of international software developers gather at the Vienna Imperial Castle (Hofburg Wien), you can feel that magic is about to happen. Exactly that occurred on November 28 and 29 at this year’s We Are Developers Congress in Vienna.
‘Are you on the Edge? Or still in the Cloud?’ – On one of the three stages, Josef Hammer inspired over 200 IT enthusiasts with a 30-minute talk on Edge Computing and 5G networks. As with the transition from mainframes to desktop computers, in the upcoming years a lot of processing will move from the cloud to the edge of the network, i.e. closer to the user. This will particularly affect areas with high data volume (IoT, AI) and low latency requirements (IoT).
Josef gave a short introduction to this exciting new area and its benefits and use cases, which frameworks and tools developers can use right now, and where we might be headed. Especially the presentation of our 5G Playground Carinthia was curiously followed by the attendees who enjoyed a first glance at the ambitious research projects conducted here.
More information:
The paper has been accepted (through double-blind peer review) as a regular paper of the Euromicro PDP’2020 conference to be held in Vasteras, Sweden on 11-13 March, 2020.
Title: M3AT: Monitoring Agents Assignment Model for Data-Intensive Applications
Authors: Vladislav Kashansky, Dragi Kimovski, Radu Prodan, Prateek Agrawal, Fabrizio Marozzo, Iuhasz Gabriel, Marek Justyna and Javier Garcia-Blas
Abstract: Nowadays, massive amounts of data are acquired, transferred, and analyzed nearly in real-time by utilizing a large number of computing and storage elements interconnected through high-speed communication networks. However, one issue that still requires research effort is to enable efficient monitoring of applications and infrastructures of such complex systems. In this paper, we introduce a Integer Linear Programming (ILP) model called M3AT for optimised assignment of monitoring agents and aggregators on large-scale computing systems. We identified a set of requirements from three representative data-intensive applications and exploited them to define the model’s input parameters. We evaluated the scalability of M3AT using the Constraint Integer Programing (SCIP) solver with default configuration based on synthetic data sets. Preliminary results show that the model provides optimal assignments for systems composed of up to 200 monitoring agents while keeping the number of aggregators constant and demonstrates variable sensitivity with respect to the scale of monitoring data aggregators and limitation policies imposed.
Keywords: Monitoring systems, high performance computing, aggregation, systems control, data-intensive systems, generalized assignment problem, SCIP optimization suite.
Acknowledgement: This work has received funding from the EC-funded project H2020 FETHPC ASPIDE (Agreement #801091)