Cluster Computing, Volume (24), No (3), Year (2021-9) , Pages (1711-1733)

Title : ( A divide and conquer approach to deadline constrained cost-optimization workflow scheduling for the cloud )

Authors: ghazaleh khojasteh , Mahmoud Naghibzadeh ,

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Abstract

The modeling of complex computational applications as giant computational workflows has been a critically effective means of better understanding the intricacies of applications and of determining the best approach to their realization. It is a challenging assignment to schedule such workflows in the cloud while also quality of service requirements. The present paper introduces a new direction based on a divide-and-conquer approach to scheduling these workflows. The proposed Divide-and-conquer Workflow Scheduling algorithm (DQWS) is designed with the objective of minimizing the cost of workflow execution while respecting its deadline. The critical path concept is the inspiration behind the divide-and-conquer process. DQWS finds the critical path, schedules it, removes the critical path from the workflow, and effectively divides the leftover into some mini workflows. The process continues until only chain structured workflows, called linear graphs, remain. Scheduling linear graphs is performed in the final phase of the algorithm. Experiments show that DQWS outperforms its competitors, both in terms of meeting deadlines and minimizing the monetary costs of executing scheduled workflows

Keywords

, Workflow scheduling; cloud computing; critical path; divide, and, conquer
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@article{paperid:1082803,
author = {Khojasteh, Ghazaleh and Naghibzadeh, Mahmoud},
title = {A divide and conquer approach to deadline constrained cost-optimization workflow scheduling for the cloud},
journal = {Cluster Computing},
year = {2021},
volume = {24},
number = {3},
month = {September},
issn = {1386-7857},
pages = {1711--1733},
numpages = {22},
keywords = {Workflow scheduling; cloud computing; critical path; divide-and-conquer},
}

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%0 Journal Article
%T A divide and conquer approach to deadline constrained cost-optimization workflow scheduling for the cloud
%A Khojasteh, Ghazaleh
%A Naghibzadeh, Mahmoud
%J Cluster Computing
%@ 1386-7857
%D 2021

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