Cutting Your Cloud Computing Cost for Deadline-Constrained Batch Jobs

被引:8
|
作者
Yao, Min [1 ]
Zhang, Peng [2 ]
Li, Yin [1 ]
Hu, Jie [1 ]
Lin, Chuang [1 ]
Li, Xiang-Yang [3 ]
机构
[1] Tsinghua Univ, Dept Comp Sci & Technol, Tsinghua Natl Lab Informat Sci & Technol TNList, Beijing 100084, Peoples R China
[2] Xi An Jiao Tong Univ, Dept Comp Sci & Technol, Xian 710049, Peoples R China
[3] IIT, Dept Comp Sci, Chicago, IL 60616 USA
关键词
D O I
10.1109/ICWS.2014.56
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Many web service providers use commercial cloud computing infrastructures like Amazon for flexible and reliable service deployment. For these web service providers, the cost of cloud computing usage becomes a big part of their IT department cost. Facing the diverse pricing models including on-demand, reserved, and spot instance, it is difficult for web service providers to optimize their cost. This paper introduces a new cloud brokerage service to help web service providers to minimize their cloud computing cost for deadline-constrained batch jobs, which have been a significant workload in web services. Our cloud brokerage service associates each batch job with deadline, and always tries to use cheaper reserved instances for computation to maintain a minimum cost. We achieve this with the following two steps: (1) given a set of jobs' specifications, determine the scheduling of jobs; (2) given the scheduling and pricing options, find an optimal instance renting strategy. We prove that both problems in two steps are computation intractable, and propose approximation algorithms for them. Trace-based evaluation shows that our cloud brokerage service can reduce up to 57% of the cloud computing cost.
引用
收藏
页码:337 / 344
页数:8
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