Workflow partitioning and deployment on the cloud using Orchestra

Ward Jaradat, Alan Dearle, Adam Barker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)
4 Downloads (Pure)


Orchestrating service-oriented workflows is typically based on a design model that routes both data and control through a single point -- the centralised workflow engine. This causes scalability problems that include the unnecessary consumption of the network bandwidth, high latency in transmitting data between the services, and performance bottlenecks. These problems are highly prominent when orchestrating workflows that are composed from services dispersed across distant geographical locations. This paper presents a novel workflow partitioning approach, which attempts to improve the scalability of orchestrating large-scale workflows. It permits the workflow computation to be moved towards the services providing the data in order to garner optimal performance results. This is achieved by decomposing the workflow into smaller sub workflows for parallel execution, and determining the most appropriate network locations to which these sub workflows are transmitted and subsequently executed. This paper demonstrates the efficiency of our approach using a set of experimental workflows that are orchestrated over Amazon EC2 and across several geographic network regions.
Original languageEnglish
Title of host publication7th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2014)
Number of pages10
ISBN (Electronic)9781479978816
Publication statusPublished - 15 Feb 2015


  • Service-orientated
  • Workflows
  • Orchestration
  • Partitioning
  • Computation placement analysis
  • Deployment


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