The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Improving Energy-Efficiency of Computational Grids via Scheduling
|
|
Author(s): Ziliang Zong (South Dakota School of Mines and Technology, USA), Xiaojun Ruan (Auburn University, USA), Adam Manzanares (Auburn University, USA), Kiranmai Bellam (Auburn University, USA)and Xiao Qin (Auburn University, USA)
Copyright: 2010
Pages: 24
Source title:
Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies and Applications
Source Author(s)/Editor(s): Nick Antonopoulos (University of Derby, UK), Georgios Exarchakos (University of Surrey, UK), Maozhen Li (Brunel University, UK)and Antonio Liotta (Technical University of Eindhoven, The Netherlands)
DOI: 10.4018/978-1-61520-686-5.ch022
Purchase
|
Abstract
High performance Grid platforms and parallel computing technologies are experiencing their golden age because of the convergence of four critical momentums: high performance microprocessors, high-speed networks, free middleware tools, and highly increased needs of computing capability. We are witnessing the rapid development of computational Grid technologies. Dozens of exciting Grid infrastructures and projects like Grid-tech, Grid Portals, Grid Fora, and Commercial Grid Initiatives are being built all over the world. However, the fast growing power consumption of data centers has caused serious concerns for building more large-scale supercomputers, clusters, and Grids. Therefore, designing energy-efficient computational Grids to make them economically attractive and environmentally friendly for parallel applications becomes highly desirable. Unfortunately, most previous studies in Grid computing primarily focus on the improvement of performance, security, and reliability, while completely ignoring the energy conservation issue. To address this problem, we propose a general architecture for building energy-efficient computational Grids and discuss the potential possibilities for incorporating power-aware techniques to different layers of the proposed Grid architecture. In this chapter, we first provide necessary background on computational Grids, Grid computing, and parallel scheduling. Next, we illustrate the general Grid architecture and explain the functionality of different layers. Followed by that, we discuss the design and implementation details of applying the energy-efficient job-scheduling technique, which is called Communication Energy Conservation Scheduling (or CECS for short), to computational Grids. Finally, we present extensive simulation results to prove the improvement of energy-efficiency of computational Grids.
Related Content
|
Radhika Kavuri, Satya kiranmai Tadepalli.
© 2024.
19 pages.
|
|
Ramu Kuchipudi, Ramesh Babu Palamakula, T. Satyanarayana Murthy.
© 2024.
10 pages.
|
|
Nidhi Niraj Worah, Megharani Patil.
© 2024.
21 pages.
|
|
Vishal Goar, Nagendra Singh Yadav.
© 2024.
23 pages.
|
|
S. Boopathi.
© 2024.
24 pages.
|
|
Sai Samin Varma Pusapati.
© 2024.
25 pages.
|
|
Swapna Mudrakola, Krishna Keerthi Chennam, Shitharth Selvarajan.
© 2024.
11 pages.
|
|
|