NDLI: Workflow Partitioning and Deployment on the Cloud Using Orchestra

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Publisher's Information

Workflow Partitioning and Deployment on the Cloud Using Orchestra

Content Provider	ACM Digital Library
Author	Dearle, Alan Jaradat, Ward Barker, Adam
Abstract	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.
Starting Page	251
Ending Page	260
Page Count	10
File Format	PDF
ISBN	9781479978816
DOI	10.1109/UCC.2014.34
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-12-08
Access Restriction	Subscribed
Subject Keyword	Service-oriented workflows orchestration partitioning computation placement analysis deployment
Content Type	Text
Resource Type	Article

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