09:10 | Opening |
09:15 | Demand-aware and distributed cloud networking: Let’s get physical! Stefan Schmid (University of Vienna, Austria) |
10:00 | Morning coffee break |
10:30 | Machine Learning Training: Research Challenges and Opportunities for Distributed Computing Giovanni Neglia (Inria Sophia Antipolis, France) |
11:15 | Towards autonomous industries Robert Birke (ABB Corporate Research, Switzerland) |
12:00 | Lunch break |
14:00 | Resilience at the Edge Ivona Brandić (Vienna University of Technology, Austria) |
14:45 | End-to-end Orchestration Automation in Distributed Cloud: Resource, Service and Multi-stakeholders Aspects Róbert Szabó (Ericsson Research, Hungary) |
15:30 | Practical Network Monitoring in Software Switches Roy Friedman (Technion – Israel Institute of Technology, Israel) |
16:15 | Afternoon coffee break |
16:45 | The Distributed Cloud: Theory Meets Practice Panel |
Invited Speakers
Dr. Robert Birke (ABB Corporate Research, Switzerland)
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Talk title: Towards autonomous industries |
Talk abstract: Digitalization and autonomy are shaping the fourth industrial revolution. This revolution relies on many technological corner stones including computing, e.g., fog computing, networking, e.g., 5G, and algorithms, e.g., deep learning. Some of these technologies are shared with consumer applications, however industrial requirements and boundary conditions can significantly differ in many respects. This talk will present the requirements from an industrial perspective leading to more autonomous industries and pinpoint some of the main research challenges relevant to the industrial setting. |
Prof. Ivona Brandić (Vienna University of Technology, Austria)
![]() From 2002 to 2007 she was Assistant Professor at the Department of Scientific Computing, University of Vienna. Form 2007 to 2014 she was Assistant Professor at the Institute of Information Systems, TU Vienna. From 2014 to 2015 she was Assistant Professor at the Institute for Software Technology and Interactive Systems. She received her PhD degree in 2007 and her venia docendi for practical computer science in 2013, both from Vienna University of Technology. From June to August 2008 she was visiting researcher at the University of Melbourne, Australia. I. Brandic is on the Editorial Board of the IEEE Transactions on Cloud Computing, IEEE Magazine on Cloud Computing and IEEE Transactions on Parallel and Distributed Systems. In 2011 she received the Distinguished Young Scientist Award from the Vienna University of Technology for her project on the Holistic Energy Efficient Hybrid Clouds. Her interests comprise virtualized HPC systems, energy efficient ultra-scale distributed systems, massive-scale data analytics, Cloud & workflow Quality of Service (QoS), and service-oriented distributed systems. She published more than 50 scientific journal, magazine and conference publications and she co-authored a text-book on federated and self-manageable Cloud infrastructures. She has been serving more than 50 program committees among others Supercomputing, CCGrid, CloudCom, EuroPar, and COMPSAC. |
Talk title: Resilience at the Edge |
Talk abstract: Internet of Things (IoT) is revolutionizing the way how information is processed and stored. Due to latency sensitive applications and huge amounts of data produced at the edge of the network, more and more data is processed where it is produced – namely on the edge. This development results in completely new network topologies where besides massive data centers we experience growing amount of so called micro data centers on the edge of the network. However, increasing complexity of multiple data centers necessary to execute an application represents a new challenge for the deployment and runtime operation of large scale applications like those in the area of smart cities, self-driving vehicles and tele medicine. The challenge thereby is to deploy application in a way to satisfy user requirements in form of different Quality of Service parameters (e.g., latency) but at the same time minimize energy consumption necessary to execute the application. In this talk we discuss challenges considering resilience that arise when deploying near real time analytics on the edge of the network. |
Prof. Roy Friedman (Technion – Israel Institute of Technology, Israel)
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Talk title: Practical Network Monitoring in Software Switches |
Talk abstract: Recent trends such as Network Function Virtualization (NFV), Software Defined Networks (SDN) and multi-tenant virtual machine hosting imply that many network functions, which were traditionally realized in hardware, must now be implemented in software. Measuring and monitoring network statistics are extremely important functions, as they enable effective traffic engineering, load balancing, caching, and security. Yet, developing such capabilities in software is tricky, especially given the ever-increasing line rates of modern networks. While SRAM memory, which is fast enough to cope line rates, is larger in modern servers’ CPUs than in switches, it is still far from being abundant. On the other hand, software lacks the fine grain massive parallelism that hardware designs benefit from. This means that naïve implementations of sketches and similar traditional techniques do not perform well in software. In this talk I will exemplify the challenges in designing fast network measurements and monitoring functions in software. I will then present some recent results about how to effectively combine sampling and sketching techniques in order to meet these challenges. |
Dr. Giovanni Neglia (Inria Sophia Antipolis, France)
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Talk title: Machine Learning Training: Research Challenges and Opportunities for Distributed Computing |
Talk abstract: We explain why existing general-purpose computation frameworks like Spark are rarely used to train large machine learning models, and introduce parameter server and ring-allreduce, the most common paradigms for distributed machine learning training. We motivate the need for research from the distributed systems’ community and present some recent directions pursued in our team on adaptive backup workers and communication topology design. |
Prof. Stefan Schmid (University of Vienna, Austria)
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Talk title: Demand-aware and distributed cloud networking: Let’s get physical! |
Talk abstract: Networks from, to and inside datacenters have become a critical infrastructure of our digital society. In order to improve the efficiency of these networks, over the last years, researchers have put major efforts into increasing the flexibility of the underlying communication technologies, enabling demand-awareness on different layers, from the application layer down to the networking layer. Enabled by novel reconfigurable optical technologies, the physical layer now emerges as a next frontier where demand-awareness can be introduced. In this talk, I will present the vision, enablers, motivation, metrics, and algorithmic challenges of demand-aware networks. In particular, I will present a distributed self-adjusting cloud network which provides route lengths that meet entropy lower bounds. |
Dr. Róbert Szabó (Ericsson Research, Hungary)
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Talk title: End-to-end orchestration automation in distributed cloud: resource, service and multi-stakeholders aspects |
Talk abstract: Edge computing provides compute and storage resources with adequate connectivity (networking) close to the devices generating / terminating traffic. The benefit is the ability to provide new services with strict requirements on, e.g., latency, bandwidth or on local break-out possibilities. Many use-cases for 5G (IoT, connected cars, Industry 4.0, …) span the device, access-, distributed-, national- or global sites. This requires a solution that can handle any workload, anywhere in the network, with end-to-end orchestration. Distributed cloud goes along with automated deployment of applications at just the right location in the network to optimize resource efficiency and user experience. Distributed clouds, however, may well span across multiple providers, both infrastructure and online service providers, and may include enterprises or end customer resources too. In such scenarios, autonomous systems shall self-organize themselves into situational orchestration structures (hierarchies) to enable end-to-end automation. Last but not least applications are built on top of multiple-layers of services, which may be managed on their own (XaaS paradigm). How distributed resources and managed services from multiple-stakeholders may be brought together for end-to-end service automation is discussed based on results and insights gained from a proof of concept research prototype. |