Uncovering the Perfect Place: Optimising Workflow Engine Deployment in the Cloud

TL;DR

This paper introduces CloudForecast, a framework that predicts the optimal cloud region for deploying workflow engines to minimize execution time, achieving significant speedups in distributed web service workflows.

Contribution

The paper presents a novel analysis tool that uses network metrics to automatically determine the best cloud deployment region for workflow engines.

Findings

Average speedup of 82.25% in workflow execution time

Effective prediction of optimal deployment regions based on network metrics

Significant performance improvements demonstrated in experiments

Abstract

When orchestrating highly distributed and data-intensive Web service workflows the geographical placement of the orchestration engine can greatly affect the overall performance of a workflow. We present CloudForecast: a Web service framework and analysis tool which, given a workflow specification, computes the optimal Amazon EC2 Cloud region to automatically deploy the orchestration engine and execute the workflow. We use geographical distance of the workflow, network latency and HTTP round-trip time between Amazon Cloud regions and the workflow nodes to find a ranking of Cloud regions. This overall ranking predicts where the workflow orchestration engine should be deployed in order to reduce overall execution time. Our experimental results show that our proposed optimisation strategy, depending on the particular workflow, can speed up execution time on average by 82.25% compared to local execution.