Policy-Aware Optimization of Parallel Execution of Composite Services

Mai Trang, Yohei Murakami, Toru Ishida

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Parallel execution and cloud technologies are the keys to speed-up service invocation when processing largescale data. In SOA, service providers normally employ policies to limit parallel execution of the services based on arbitrary decisions. In order to attain optimal performance improvement, service users need to adapt to parallel execution policies of the services. A composite service is a combination of several atomic services provided by various providers. To use parallel execution for greater composite service efficiency we need to optimize the degree of parallelism (DOP) of the composite services by considering policies of all atomic services. We propose a model that embeds service policies into formulae to calculate composite service performance. From the calculation, we predict the optimal DOP for the composite service. Extensive experiments are conducted on real-world translation services. The results show that our proposed model has good prediction accuracy in identifying the optimal DOPs. Our model correctly predicts the optimal DOP in most cases.

Original languageEnglish
JournalIEEE Transactions on Services Computing
DOIs
Publication statusAccepted/In press - 2015 Aug 12
Externally publishedYes

Keywords

  • Big Data
  • Computational modeling
  • Google
  • Mathematical model
  • Parallel Execution
  • Parallel processing
  • Predictive models
  • Quality of service
  • Service Composition
  • Service Policy
  • Service-oriented architecture

ASJC Scopus subject areas

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

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