On scheduling of high-throughput scientific workflows under budget constraints in multi-cloud environments

Document Type

Conference Proceeding

Publication Date

7-2-2018

Abstract

With the rapid development and deployment of cloud computing infrastructures, many applications in various scientific domains are increasingly utilizing cloud resources for big data storage and analysis. Particularly, it has become a significant challenge to manage and execute big data scientific workflows in multi-cloud environments to process streaming datasets. In this paper, within a three-layer workflow architecture with inter-and intra-cloud data transfer, we formulate a scientific workflow mapping problem under budget constraints to achieve the maximum throughput of streaming workflow applications. We propose a scheduling algorithm to identify the global bottleneck and maximize the throughput under budget constraints. Extensive simulation results show that the proposed algorithm exhibits superior performance over existing heuristic algorithms in scheduling streaming workflow applications.

Identifier

85063883250 (Scopus)

ISBN

[9781728111414]

Publication Title

Proceedings 16th IEEE International Symposium on Parallel and Distributed Processing with Applications 17th IEEE International Conference on Ubiquitous Computing and Communications 8th IEEE International Conference on Big Data and Cloud Computing 11th IEEE International Conference on Social Computing and Networking and 8th IEEE International Conference on Sustainable Computing and Communications Ispa Iucc Bdcloud Socialcom Sustaincom 2018

External Full Text Location

https://doi.org/10.1109/BDCloud.2018.00162

First Page

1087

Last Page

1094

Grant

2018GY-011

Fund Ref

Northwest University

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