بایگانی برچسب برای: scheduling

A Hybrid Real-Time Scheduling Approach for Large-Scale[taliem.ir]

A Hybrid Real-Time Scheduling Approach for Large-Scale Multicore Platforms

We propose a hybrid approach for scheduling real-time tasks on large-scale multicore platforms with hierarchical shared caches. In this approach, a multicore platform is partitioned into clusters. Tasks are statically assigned to these clusters, and scheduled within each cluster using the preemptive global EDF scheduling algorithm. We show that this hybrid of partitioning and global scheduling performs better on large-scale platforms than either approach alone. We also determine the appropriate cluster size to achieve the best performance possible, given the characteristics of the task set to be supported.
Effcient Resource Management for Cloud[taliem.ir]

Effcient Resource Management for Cloud Computing Environments

The notion of Cloud computing has not only reshaped the feld of distributed systems but also fundamentally changed how businesses utilize computing today. While Cloud computing provides many advanced features, it still has some shortcomings such as the relatively high operating cost for both public and private Clouds. The area of Green computing is also becoming increasingly important in a world with limited energy resources and an ever-rising demand for more computational power. In this paper a new framework is presented that provides efcient green enhancements within a scalable Cloud computing architecture. Using power-aware scheduling techniques, variable resource management, live migration, and a minimal virtual machine design, overall system efciency will be vastly improved in a data center based Cloud with minimal performance overhead.
Classification of Future Electricity Market Prices[taliem.ir]

Classification of Future Electricity Market Prices

Forecasting short-term electricity market prices has been the focus of several studies in recent years. Although various approaches have been examined, achieving sufficiently low forecasting errors has not been always possible. However, certain applications, such as demand-side management, do not require exact values for future prices but utilize specific price thresholds as the basis for making short-term scheduling decisions. In this paper, classification of future electricity market prices with respect to prespecified price thresholds is introduced. Two alternative models based on support vector machines are proposed in a multi-class, multi-step-ahead price classification context. Numerical results are provided for classifying prices in Ontario’s and Alberta’s markets.