D
David Abramson
Researcher at University of Queensland
Publications - 291
Citations - 10754
David Abramson is an academic researcher from University of Queensland. The author has contributed to research in topics: Grid & Grid computing. The author has an hindex of 39, co-authored 287 publications receiving 10544 citations. Previous affiliations of David Abramson include University of Lincoln & Monash University.
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Proceedings ArticleDOI
Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid
TL;DR: The proposed Nimrod/G grid-enabled resource management and scheduling system builds on the earlier work on Nimrod and follows a modular and component-based architecture enabling extensibility, portability, ease of development, and interoperability of independently developed components.
Journal ArticleDOI
Economic models for resource management and scheduling in Grid computing
TL;DR: A computational economy framework for resource allocation and for regulating supply and demand in Grid computing environments is proposed and some of the economic models in resource trading and scheduling are demonstrated using the Nimrod/G resource broker.
Proceedings Article
High performance parametric modeling with Nimrod/G: Killer application for the global grid?
TL;DR: The role of parametric modeling as an application for the global computing grid is examined, and some heuristics which make it possible to specific soft real time deadlines for larger computational experiments are explored.
Journal ArticleDOI
The Grid Economy
TL;DR: An extensive, service-oriented Grid architecture driven by Grid economy and an approach for its realization by leveraging various existing Grid technologies are presented and commodity and auction models for resource allocation are presented.
Journal ArticleDOI
A computational economy for grid computing and its implementation in the Nimrod-G resource broker
TL;DR: The authors' service-oriented grid computing system called Nimrod-G manages all operations associated with remote execution including resource discovery, trading, scheduling based on economic principles and a user-defined QoS requirement.