Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Grid benchmarking: vision, challenges, and current status: Research Articles
Concurrency and Computation: Practice & Experience
Speed scaling to manage energy and temperature
Journal of the ACM (JACM)
Energy-aware scheduling for real-time multiprocessor systems with uncertain task execution time
Proceedings of the 44th annual Design Automation Conference
Harnessing Green IT: Principles and Practices
IT Professional
How are Real Grids Used? The Analysis of Four Grid Traces and Its Implications
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
JMT: performance engineering tools for system modeling
ACM SIGMETRICS Performance Evaluation Review
Energy Profiling and Analysis of the HPC Challenge Benchmarks
International Journal of High Performance Computing Applications
The GREEN-NET framework: Energy efficiency in large scale distributed systems
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Proceedings of the 46th Annual Design Automation Conference
Cooperative power-aware scheduling in grid computing environments
Journal of Parallel and Distributed Computing
Modeling job arrivals in a data-intensive grid
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
Energy-efficient server clusters
PACS'02 Proceedings of the 2nd international conference on Power-aware computer systems
EPEW'07 Proceedings of the 4th European performance engineering conference on Formal methods and stochastic models for performance evaluation
Performance evaluation of bag of gangs scheduling in a heterogeneous distributed system
Journal of Systems and Software
Job-resource matchmaking on Grid through two-level benchmarking
Future Generation Computer Systems
Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures
ICDCS '10 Proceedings of the 2010 IEEE 30th International Conference on Distributed Computing Systems
Making a case for a green500 list
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
IEEE Internet Computing
Layered Green Performance Indicators
Future Generation Computer Systems
Energy efficient utilization of resources in cloud computing systems
The Journal of Supercomputing
A three-phase energy-saving strategy for cloud storage systems
Journal of Systems and Software
The Journal of Supercomputing
A study on combinational effects of job and resource characteristics on energy consumption
Multiagent and Grid Systems
| Hi-index | 0.00 |
Complex distributed architectures, like Grid, supply effective platforms to solve computations on huge datasets, often at the cost of increased power consumption. This energy issue affects the sustainability of the infrastructures and increases their environmental impact. On the other hand, due to Grid heterogeneity and scalability, possible power savings could be achieved if effective energy-aware allocation policies were adopted. These policies are meant to implement a better coupling between application requirements and the Grid resources, also taking energy parameters into account. In this paper, we discuss different allocation strategies which address jobs submitted to Grid resources, subject to efficiency and energy constraints. Our aim is to analyze the potential benefits that can be obtained from the adoption of a metric able to capture both performance and energy-savings. Based on an experimental study, we simulated two alternative scenarios aimed at comparing the behavior of different strategies for allocating jobs to resources. Moreover we introduced the Performance/Energy Trade-off function as a useful means to evaluate the tendency of an allocation strategy toward efficiency or power consumption. Our conclusion seems to suggest that performance and energy-savings are not always enemies, and these objectives may be combined if suitable energy metrics are adopted.