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

Jun HUANG  Yanbing LIU  Ruozhou YU  Qiang DUAN  Yoshiaki TANAKA  

Publication
IEICE TRANSACTIONS on Communications   Vol.E96-B   No.1   pp.10-19
Publication Date: 2013/01/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.E96.B.10
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Section on Network Virtualization, and Fusion Platform of Computing and Networking)
Category: 
Keyword: 
cloud service provisioning,  network virtualization,  quality of service,  service composition,  approximation algorithm,  

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Summary: 
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.