Breathing in the Clouds - Thin Air or Bad Atmosphere?
Gottfried Vossen, DBIS Group, University of Münster, Germany
Reducing Energy Consumption by using Clouds
Ivona Brandić, TU Wien
Favoritenstr. 9-11, Vienna UT, Austria
Data Science, Clouds and X-Informatics
Geoffrey C. Fox, Indiana University, United States
Breathing in the Clouds - Thin Air or Bad Atmosphere?
Gottfried Vossen
DBIS Group, University of Münster
Germany
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Brief Bio
Gottfried Vossen is a Professor of Computer Science in the Department of Information Systems at the University of Muenster in Germany, a Fellow of the German Computer Science Society, and an Honorary Professor at the University of Waikato Management School in Hamilton, New Zealand. He received his master´s and Ph.D. degrees as well as the German habilitation in 1981, 1986, and 1990, resp., all from the Technical University of Aachen in Germany. He is the European Editor-in-Chief of Elsevier's Information Systems - An International Journal, and has held visiting positions at various universities in Germany and abroad. His research interests include conceptual as well as application-oriented problems concerning databases, information systems, process modeling, and various forms of Web 2.0 applications, cloud computing, big data, as well as implications. He has been member in numerous program committees of international conferences and workshops. He is an author or co-author of more than 200 publications, and an author, co-author, or co-editor of more than 20 books on databases, business process modeling, the Web, e-commerce, cloud computing, and computer architecture.
Abstract
Cloud computing has become everyday business for smartphone users, and it has become big business for a number of providers of computer-related resources. While large companies as well as many start-ups are already enjoying the cloud benefits, small and medium enterprises (SMEs) are often still hesitating to move their IT business to the cloud. This talk will start with an identification of cloud-sourcing properties as well as from various success stories of cloud usage. It will then look at what might make the air thin when in the clouds and what could make the atmosphere bad. Proper exploitation, however, can make a difference even for SMEs, and enables a number of new applications that we have seen emerging in recent years, among them big data processing, for example in the automotive and health sectors, or data marketplaces. As a conclusion, it will be argued that the cloud is not reversible, and that we better start breathing normally again!
Reducing Energy Consumption by using Clouds
Ivona Brandić
TU Wien
Favoritenstr. 9-11, Vienna UT
Austria
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Brief Bio
Dr. Ivona Brandic is Assistant Professor at the Distributed Systems Group, Information Systems Institute, Vienna University of Technology (TU Wien). Prior to that, she was Assistant Professor at the Department of Scientific Computing, Vienna University. She received her PhD degree from Vienna University of Technology in 2007. From 2003 to 2007 she participated in the special research project AURORA - Advanced Models, Applications and Software Systems for High Performance Computing and the European Union's GEMSS - Grid-Enabled Medical Simulation Services project. She is involved in the European Union's SCube project and she is leading the Austrian national FoSII - Foundations of Self-governing ICT Infrastructures project funded by the Vienna Science and Technology Fund (WWTF). She is management committee member of the European Commission's COST Action on Energy Efficient Large Scale Distributed Systems. From June to August 2008 she was visiting researcher at the University of Melbourne, Australia.
In 2011 she received the Distinguished Young Scientist Award from the Vienna University of Technology for her HALEY project on Holistic Energy Efficient Hybrid Clouds. Her interests comprise Service Level Agreement and Quality of Service management in large scale distributed systems, autonomic computing, workflow management for scientific applications, and energy efficient large scale distributed systems (Cloud, Grid, Cluster, etc.). She published more than 50 scientific journal, magazine and conference publications and co-authored a text book on federated and self-manageable Cloud infrastructures. I. Brandic co-authored European Union's Cloud Computing report paving future research directions of the EU. In 2010 she chaired the International Conference on Utility and Cloud Computing held in Chennai, India. She has been serving more than 50 program committees (among others EuroPar, COMPSAC, CloudCom) and was invited reviewer of more than 10 international journals. In 2011 she edited two special issues for Future Generation Computer Systems (Elsevier) and Scientific Programming Journal (IOS Press). I. Brandic has been invited expert evaluator of the European Commission, French National Research Organization (ANR), National Science and Engineering Research Council Canada (NSERC) and Netherlands Organization for Scientific Research (NWO).
Abstract
Cloud computing is a promising technology for the realization of large, scalable, and on-demand provisioned computing infrastructures. Currently, many enterprises are adopting Clouds to achieve high performance and scalability for their applications while maintaining low costs. Service provisioning in the Cloud is based on a set of predefined non-functional properties specified and negotiated by means of Service Level Agreements (SLAs). Cloud workloads are dynamic and change constantly. Thus, in order to reduce steady human interactions, self-manageable Cloud techniques are required to comply with the agreed customers’ SLAs.
In this talk we discuss flexible and reliable management of SLAs, which is of paramount importance for both, Cloud providers and consumers. On the one hand, the prevention of SLA violations avoids penalties that are costly to providers. On the other hand, based on flexible and timely reactions to possible SLA violation threats, user interaction with the system can be minimized enabling Cloud computing to take roots as a flexible and reliable form of on-demand computing. Furthermore, a trade-off has to be found between proactive actions that prevent SLA violations and those that reduce energy consumption, i.e., increase energy efficiency.
Data Science, Clouds and X-Informatics
Geoffrey C. Fox
Indiana University
United States
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Brief Bio
Geoffrey Charles Fox (gcf@indiana.edu, http://www.infomall.org, http://www.futuregrid.org)Fox received a Ph.D. in Theoretical Physics from Cambridge University and is now distinguished professor of Informatics and Computing, and Physics at Indiana University where he is director of the Digital Science Center and Associate Dean for Research and Graduate Studies at the School of Informatics and Computing. He previously held positions at Caltech, Syracuse University and Florida State University. He has supervised the PhD of 64 students and published over 600 papers in physics and computer science with an hindex of 61 and over 19500 citations. He currently works in applying computer science to Bioinformatics, Defense, Earthquake and Ice-sheet Science, Particle Physics and Chemical Informatics. He is principal investigator of FutureGrid – a facility to enable development of new approaches to computing. He is involved in several projects to enhance the capabilities of Minority Serving Institutions.
Abstract
We explore the principle that much of “the future” is driven by “Using Clouds running Data Analytics processing Big Data to solve problems in X-Informatics”. Applications (values of X) include already Astronomy, Biology, Biomedicine, Business, Chemistry, Crisis, Energy, Environment, Finance, Health, Intelligence, Lifestyle, Marketing, Medicine, Pathology, Policy, Radar, Security, Sensor, Social, Sustainability, Wealth and Wellness with more fields being defined. We discuss the implications for education and research. Education requires new curricula – generically called data science – which will be hugely popular due to the many millions of jobs opening up in both “core technology” and within applications where of course there are most opportunities. We discuss possibility of using MOOC’s to jumpstart field. On research side, big data (i.e. large applications) require big (i.e. scalable) algorithms on big infrastructure running robust convenient programming environments. We discuss clustering and information visualization using dimension reduction as examples of scalable algorithms. We compare Message Passing Interface MPI and extensions of MapReduce as the core technology to execute data analytics.