Desktop grids are popular platforms for high throughput applications, but due their inherent resource volatility it is difficult to exploit them for applications that require rapid turnaround. Efficient desktop grid execution of short-lived applications is an attractive proposition and we claim that it is achievable via intelligent resource selection. We propose three general techniques for resource selection: resource prioritization, resource exclusion, and task duplication. We use these techniques to instantiate several scheduling heuristics. We evaluate these heuristics through trace-driven simulations of four representative desktop grid configurations. We find that ranking desktop resources according to their clock rates, without taking...
AbstractTo harvest idle, unused computational resources in networked environments, researchers have ...
International audienceIn this paper, we study the execution of iterative applications on volatile pr...
Desktop grids use opportunistic sharing to exploit large collections of personal computers and works...
Desktop grids are popular platforms for high through-put applications, but due their inherent resour...
Desktop Grids have proved to be a suitable platform for the execution of Bag-of-Tasks applications b...
In this paper, we present a checkpoint-based scheme to improve the turnaround time of bag-of-tasks a...
Desktop Grids have proved to be a suitable platform for the execution of Bag-of-Tasks applications b...
Desktop grid computing has emerged from the concept of providing relatively large amounts of computi...
Desktop grids are compute platforms that aggregate and harvest the idle CPU cycles of individually o...
Desktop Grids have emerged as an important method-ology to harness the idle cycles of millions of pa...
In this paper we propose a novel framework for the dynamic allocation of jobs in grid-like environme...
This paper addresses a resource selection problem for applications that update data in enterprise gr...
Resource management effective scheduling algorithms is also increasing rapidly, particularly in the ...
Desktop grid is a relatively new trend in grid computing. As opposed to traditional (service based) ...
Desktop resources are attractive for running compute-intensive distributed applications. Several sys...
AbstractTo harvest idle, unused computational resources in networked environments, researchers have ...
International audienceIn this paper, we study the execution of iterative applications on volatile pr...
Desktop grids use opportunistic sharing to exploit large collections of personal computers and works...
Desktop grids are popular platforms for high through-put applications, but due their inherent resour...
Desktop Grids have proved to be a suitable platform for the execution of Bag-of-Tasks applications b...
In this paper, we present a checkpoint-based scheme to improve the turnaround time of bag-of-tasks a...
Desktop Grids have proved to be a suitable platform for the execution of Bag-of-Tasks applications b...
Desktop grid computing has emerged from the concept of providing relatively large amounts of computi...
Desktop grids are compute platforms that aggregate and harvest the idle CPU cycles of individually o...
Desktop Grids have emerged as an important method-ology to harness the idle cycles of millions of pa...
In this paper we propose a novel framework for the dynamic allocation of jobs in grid-like environme...
This paper addresses a resource selection problem for applications that update data in enterprise gr...
Resource management effective scheduling algorithms is also increasing rapidly, particularly in the ...
Desktop grid is a relatively new trend in grid computing. As opposed to traditional (service based) ...
Desktop resources are attractive for running compute-intensive distributed applications. Several sys...
AbstractTo harvest idle, unused computational resources in networked environments, researchers have ...
International audienceIn this paper, we study the execution of iterative applications on volatile pr...
Desktop grids use opportunistic sharing to exploit large collections of personal computers and works...