You are not logged in.

Converged network-cloud service composition with end-to-end performance guarantee

Huang, Jun, Duan, Qiang, Guo, Song, Yan, Yuhong and Yu, Shui 2015, Converged network-cloud service composition with end-to-end performance guarantee, IEEE transactions on cloud computing, vol. PP, no. 99, pp. 1-15, doi: 10.1109/TCC.2015.2491939.

Attached Files
Name Description MIMEType Size Downloads

Title Converged network-cloud service composition with end-to-end performance guarantee
Author(s) Huang, Jun
Duan, Qiang
Guo, Song
Yan, Yuhong
Yu, Shui
Journal name IEEE transactions on cloud computing
Volume number PP
Issue number 99
Start page 1
End page 15
Total pages 15
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2015-01-01
ISSN 2168-7161
Keyword(s) Cloud computing
Service-Oriented Architecture (SOA)
Network-as-a-Service (NaaS)
service composition
Quality-of-Service (QoS)
Summary The crucial role of networking in Cloud computing calls for federated management of both computing and networkin resources for end-To-end service provisioning. Application of the Service-Oriented Architecture (SOA) in both Cloud computing an networking enables a convergence of network and Cloud service provisioning. One of the key challenges to high performanc converged network-Cloud service provisioning lies in composition of network and Cloud services with end-To-end performanc guarantee. In this paper, we propose a QoS-Aware service composition approach to tackling this challenging issue. We first present system model for network-Cloud service composition and formulate the service composition problem as a variant of Multi-Constraine Optimal Path (MCOP) problem. We then propose an approximation algorithm to solve the problem and give theoretical analysis o properties of the algorithm to show its effectiveness and efficiency for QoS-Aware network-Cloud service composition. Performanc of the proposed algorithm is evaluated through extensive experiments and the obtained results indicate that the proposed metho achieves better performance in service composition than the best current MCOP approaches Service (QoS).
Language eng
DOI 10.1109/TCC.2015.2491939
Field of Research 080109 Pattern Recognition and Data Mining
080599 Distributed Computing not elsewhere classified
080399 Computer Software not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30088666

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 1 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 68 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Thu, 10 Nov 2016, 10:24:28 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.