Time: Wednesday June 1, 13-14
Place: Room 0.2.11
Talk by Verena Kantere
Abstract:
The term ‘cloud computing’ is nowadays synonymous to computing services offered by large-scale infrastructures. The key to the success of cloud computing is to provide seamless and efficient management of large dynamic disseminated data collections, such as scientific data, in order to maximize their availability while minimizing capital expenditure. This talk leverages lessons learned from financial management to solve the problem of both cost- and time-efficient management on clouds offering online data services. We propose a novel economy model for a cloud where users pay on-the-go for the data services they receive and user payments can be used for service provision, infrastructure maintenance and profit. The economy employs a cost model that takes into account all the available resources in a cloud, such as disk space and I/O operations, CPU time and network bandwidth. In order to ensure the economic viability of the cloud, the cost of offering new services has to be amortized to prospective users that will use them. We propose a novel cost amortization model that predicts the extent of amortization in time and number of users. The economy is completed with a dynamic pricing scheme that achieves optimal cloud profit while ensuring user satisfaction with service prices. The talk concludes with future research directions on the provision of online data services.
Bio:
Verena Kantere is a tenure-track lecturer at the Department of Electrical Engineering and Information Technology at the Cyprus University of Technology. She has received a Diploma (2000) and a Ph.D. (2007) from the National Techincal University of Athens, (NTUA) and a M.Sc. degree from the Department of Computer Science at the University of Toronto (2003). During her graduate studies her research interests focused on problems of data exchange and coordination in Peer-to-Peer (P2P) overlays with structured and unstructured data, as well as multidimensional data sharing. She has proposed frameworks and techniques that deal with the heterogeneity problem, query processing and rewriting, as well as managing continuous queries. Furthermore, she has shown interest and work in the field of Semantic Web, concerning the problem of semantic similarity, annotation, clustering and integration. After the completion of her PhD studies and until recently, she worked as a postdoctoral researcher (2008-2010) at the Ecole Polytechnique Federale de Lausanne (EPFL). Her research focuses on the provision of cloud data services, focusing on the special needs of large analytical data, such as scientific data. She is working towards the incorporation of cost in existing and new data management techniques and has designed a novel data-aware economy model for cloud data services.
