Topic 5: Parallel and distributed data management

The ever-increasing data volumes used to empower contemporary data-intensive applications as well as aggregations of computing systems call for novel approaches and efficient techniques in the management of geographically dispersed data. Despite recent advances, Internet-scale requirements for both applications and underlying systems require effective provisioning, staging,manipulation, continuous maintenance and monitoring of data hosted in multiple, pre-existing autonomous, distributed and often heterogeneous systems. Evidently, the notions of parallelism and concurrent execution at all levels remain key elements in attaining scalability and effective management for nearly-all modern data-intensive applications. Moreover, as underlying computing environments get transformed through the introduction of novel infrastructures, enhanced capacities and extended functionalities, new solutions are sought to cope with these changes. © 2012 Springer-Verlag