Converged Network-Cloud Service Composition with End-to-End Performance Guarantee

Jun Huang, Qiang Duan, Song Guo, Yuhong Yan, Shui Yu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)

Abstract

The crucial role of networking in cloud computing calls for federated management of both computing and networking resources for end-to-end service provisioning. Application of the Service-Oriented Architecture (SOA) in both cloud computing and networking enables a convergence of network and cloud service provisioning. One of the key challenges to high performance converged network-cloud service provisioning lies in composition of network and cloud services with end-to-end performance guarantee. In this paper, we propose a QoS-aware service composition approach to tackling this challenging issue. We first present a system model for network-cloud service composition and formulate the service composition problem as a variant of Multi-Constrained Optimal Path (MCOP) problem. We then propose an approximation algorithm to solve the problem and give theoretical analysis on properties of the algorithm to show its effectiveness and efficiency for QoS-aware network-cloud service composition. Performance of the proposed algorithm is evaluated through extensive experiments and the obtained results indicate that the proposed method achieves better performance in service composition than the best current MCOP approaches.

Original languageEnglish
Pages (from-to)545-557
Number of pages13
JournalIEEE Transactions on Cloud Computing
Volume6
Issue number2
DOIs
Publication statusPublished - 1 Apr 2018
Externally publishedYes

Keywords

  • Cloud computing
  • network-as-a-service (NaaS)
  • quality-of-service (QoS)
  • service composition
  • service-oriented architecture (SOA)

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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