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A Multi-Objective Optimization Model for Data-Intensive Workflow Scheduling in Data Grids
Publication Type:
Conference/Workshop Paper
Venue:
IEEE International LCN Workshop on Cloud-based Networks and Applications
Abstract
The concept of workflow is used for modelling many
of the data-intensive scientific applications executed on data grids.
A Workflow is a series of interdependent tasks during which data
is processed by different tasks. Scheduling the workflows in the
grids is the process of assigning tasks to appropriate resources
with the aim of achieving goals such as reducing workflow
completion time while considering the data dependencies between
the tasks. Data access time, processing time, and waiting time
together constitute task completion time in the grids. Workflow
scheduling aims to optimize these parameters in such a way that
the workflow completion time decreases, and the system efficiency
improves. In this paper, a scheduling model based on multiobjective
optimization is proposed for scheduling data-intensive
workflows in data grids. The scheduling model aims to optimize
data communication cost, waiting time, and tasks processing time
while considering data dependencies between the tasks. The model
defines the data communication cost in terms of data transfer time
in various communications between nodes (intra- and inter-cluster
communications). This study uses four different Multi-Objective
Evolutionary Algorithms (MOEAs) as well as Random Search
(RS) algorithm to implement the proposed scheduling model.
Convenient coding mechanisms for representing chromosomes,
compatible crossover and mutation operators were also designed.
Simulation results of the proposed scheduling model using
different optimization algorithms are presented. The results are
then assessed and compared based on different quality indicators.
Bibtex
@inproceedings{Helali Moghadam5094,
author = {Mahshid Helali Moghadam and Seyed Morteza Babamir and Meghdad Mirabi},
title = {A Multi-Objective Optimization Model for Data-Intensive Workflow Scheduling in Data Grids},
month = {November},
year = {2016},
booktitle = { IEEE International LCN Workshop on Cloud-based Networks and Applications },
url = {http://www.es.mdu.se/publications/5094-}
}