Advance Reservation and Revenue-based Resource Management

Advance reservation (AR) in Grid systems would allow users to guarantee resources prior to executing their jobs. This book investigates how AR can be incorporated and deployed in Grid systems, and determines how to increase resource utilization. Towards accomplishing these findings, this book provides a case for an elastic reservation model, where users can self-select or choose the best option in reserving their jobs according to their needs. In addition, this book investigates how to increase resource revenue, and examines how to regulate resource supplies and reservation demands. Towards accomplishing these inquests, this book suggests the use of Revenue Management to determine the pricing of reservations, and regulate supply and demand. Moreover, this book looks into overbooking models to protect resources against unexpected cancellations and no-shows of reservations. Finally, this book proposes the use of modeling and simulation, since various scenarios need to be evaluated and repeated. Therefore, this book describes the development of GridSim, a Grid simulation toolkit, which allows modeling and simulation of various properties.

Autorentext

Anthony Sulistio, Ph.D., has published many publications, e.g. in international journals and conferences, in the area of virtualization, Grid computing, and cloud computing. In addition, he is active in the research community by becoming a reviewer and a Program Committee to many international journals and conferences, respectively.