
The highly dynamic nature of the cloud environment leads to a time-varying resource utilization and the cloud provider can potentially accommodate secondary jobs with the remaining resource. To better implement the idea of resource reutilization in the cloud environment, the problem of secondary job scheduling with deadlines under time-varying resource capacity is considered in this paper. A transformation is proposed to reduce the offline problem with time-varying processor capacity to that with constant capacity. For online scheduling of under loaded system, it is shown that the earliest deadline first (EDF) scheduling algorithm achieves competitive ratio 1. For the overloaded system, an online scheduling algorithm V-Dover is proposed with asymptotically optimal competitive ratio when a certain admissibility condition holds. It is further shown that, in the absence of the admissibility condition, no online scheduling algorithm exists with a positive competitive ratio. Simulation results are presented to illustrate the performance advantage of the proposed V-Dover algorithm.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 11 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
