Modeling and Algorithms for QoS-Aware Service Composition in Virtualization-Based Cloud Computing

被引:11
|
作者
Huang, Jun [1 ]
Liu, Yanbing [2 ]
Yu, Ruozhou [3 ]
Duan, Qiang [4 ]
Tanaka, Yoshiaki [5 ]
机构
[1] Chongqing Univ Posts & Telecom, Sch Commun & Informat Engn, Chongqing 400065, Peoples R China
[2] Chongqing Univ Posts & Telecom, Sch Comp Sci, Chongqing 400065, Peoples R China
[3] Beijing Univ Posts & Telecom, Sch Comp Sci, Beijing 100876, Peoples R China
[4] Penn State Univ, Abington Coll, Informat Sci & Technol Dept, Abington, PA 19001 USA
[5] Waseda Univ, Global Informat & Telecommun Inst, Tokyo 1690051, Japan
基金
美国国家科学基金会;
关键词
cloud service provisioning; network virtualization; quality of service; service composition; approximation algorithm; SELECTION;
D O I
10.1587/transcom.E96.B.10
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Cloud computing is an emerging computing paradigm that may have a significant impact on various aspects of the development of information infrastructure. In a Cloud environment, different types of network resources need to be virtualized as a series of service components by network virtualization, and these service components should be further composed into Cloud services provided to end users. Therefore Quality of Service (QoS) aware service composition plays a crucial role in Cloud service provisioning. This paper addresses the problem on how to compose a sequence of service components for QoS guaranteed service provisioning in a virtualization-based Cloud computing environment. The contributions of this paper include a system model for Cloud service provisioning and two approximation algorithms for QoS-aware service composition. Specifically, a system model is first developed to characterize service provisioning behavior in virtualization-based Cloud computing, then a novel approximation algorithm and a variant of a well-known QoS routing procedure are presented to resolve QoS-aware service composition. Theoretical analysis shows that these two algorithms have the same level of time complexity. Comparison study conducted based on simulation experiments indicates that the proposed novel algorithm achieves better performance in time efficiency and scalability without compromising quality of solution. The modeling technique and algorithms developed in this paper are general and effective; thus are applicable to practical Cloud computing systems.
引用
收藏
页码:10 / 19
页数:10
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