Service Augmentation for High End Interactive Data Services

Advances in computational science, combined with the increasingly interdisciplinary and geographically distributed research teams, have led to a need to support multi-tiered, data- and meta-data-rich collaboration infrastructures. Our research addresses the interactive, remote tasks undertaken in such collaborations, which require a flexible software infrastructure able to dynamically deploy services where and when needed, and to provide data to clients in the forms in which they require it with suitable levels of end-to-end performance. The concept of service augmentation advanced in this paper seeks to continuously adjust the differences or degrees of incompatibility between the data received and the data displayed or stored by clients. Difference adjustments occur anywhere on the paths between data providers and clients, and compatibility computations leverage all of the resources that may be brought to bear, including CPUs and GPUs on servers and additional data manipulations on server, overlay, and client nodes. A formal structure and experimental evaluations of this concept are performed with the SmartPointer scientific visualization and annotation framework, for which we show that data-driven SLAs provide improved client flexibility and the ability to maintain application-specific notions of quality of service