Job allocation strategies for energy-aware and efficient Grid infrastructures

被引:14
作者
Galizia, Antonella [1 ]
Quarati, Alfonso [1 ]
机构
[1] IMATI CNR, Via Marini 6, I-16149 Genoa, Italy
关键词
Grid; Allocation policies; Energy metrics; Performance evaluation; Energy/efficiency trade-off; PERFORMANCE; MODELS;
D O I
10.1016/j.jss.2012.01.050
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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. (c) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:1588 / 1606
页数:19
相关论文
共 64 条
[1]  
ANDREOZZI S, 2008, GLUE V 2 0 REFERENCE
[2]  
[Anonymous], INT J INF MATH SCI
[3]  
[Anonymous], TR200813 DARPA
[4]  
[Anonymous], 2011, GARTNER NEWS ROOM
[5]  
[Anonymous], 2009, GLUE SPECIFICATION V
[6]  
[Anonymous], P 2010 INT C PAR DIS
[7]  
[Anonymous], 2009, ERCIM NEWS
[8]   Speed scaling to manage energy and temperature [J].
Bansal, Nikhil ;
Kimbrel, Tracy ;
Pruhs, Kirk .
JOURNAL OF THE ACM, 2007, 54 (01)
[9]  
Bao M, 2009, DES AUT CON, P490
[10]   Brokering strategies in computational grids using stochastic prediction models [J].
Berten, Vandy ;
Gaujal, Bruno .
PARALLEL COMPUTING, 2007, 33 (4-5) :238-249