Also known as “green computing”, “energy-aware computing”; similar to “power-efficient computing”, “power-aware computing”; associated in the manuscript with “energy-efficiency“, “energy consumption”, and “power consumption”.
Published in Chapter:
Improving Energy-Efficiency of Computational Grids via Scheduling
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
DOI: 10.4018/978-1-61520-686-5.ch022
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.