1. What does the Cloud mean for Data Management: Challenges and Opportunities Akrivi Vlachou Norwegian University of Science and Technology (NTNU), Trondheim, Norway

2. Yet another distributed system? Distributed databases, parallel systems, grids, peer-to-peer, … What is different in clouds? What about (multi-dimensional) distributed query processing? Process a huge amount of available data to extract useful information 2

3. Distributed Query Processing Find servers that store relevant data Query processing over local data Collect/merge partial results to an overall result set 3

4. What is different in clouds? Peer-to-Peer systems Characteristics Scalability Fault tolerance Bottlenecks Overlay network Peers are geographically distributed 4 servers disconnect only due to hardware failure each server can communicate directly with any other [log(N) hops were sufficient in P2P] not necessary true for cloud servers

5. 5 Goals of Query Processing Peer-to-Peer systems: efficiency in terms of execution time Cloud: there is a cost ($) for the service Given a maximum value for the execution time, minimize the cost ($) of the query Given a budget ($) per query, maximize the quality of the service (i.e. number of retrieved tuples)

6. Conclusions What is the new research cloud infrastructure brings to data management? How does "old" traditional research change? Mobile and distributed data management is especially relevant. What is the "cloud face" of the state of the art there?  Requirements and goals are different  existing distributed approaches should be revised  Cost of the service should be taken into account during query processing 6