Cloud Service Scheduling Algorithm Research and Optimization

Cloud Service Scheduling Algorithm Research and Optimization

We propose a cloud service scheduling model that is referred to as the Task Scheduling System (TSS). In the user module, the process time of each task is in accordance with a general distribution. In the task scheduling module, we take a weighted sum of makespan and flowtime as the objective functio...

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Main Authors: Hongyan Cui, Xiaofei Liu, Tao Yu, Honggang Zhang, Yajun Fang, Zongguo Xia
Format: Article
Language:English
Published: Hindawi-Wiley 2017-01-01
Series:Security and Communication Networks
Online Access:http://dx.doi.org/10.1155/2017/2503153
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spelling doaj-b9ff3de0f3344360aa2de9bfa6b9f2802020-11-25T01:51:45ZengHindawi-WileySecurity and Communication Networks1939-01141939-01222017-01-01201710.1155/2017/25031532503153Cloud Service Scheduling Algorithm Research and OptimizationHongyan Cui0Xiaofei Liu1Tao Yu2Honggang Zhang3Yajun Fang4Zongguo Xia5State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaState Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaInstitute of Network Science and Cyberspace, Tsinghua University, Beijing, ChinaUMass Boston, 100 William T Morrissey Boulevard, Boston, MA 02125, USAMIT CSAIL Lab, Cambridge, MA 02139, USAUMass Boston, 100 William T Morrissey Boulevard, Boston, MA 02125, USAWe propose a cloud service scheduling model that is referred to as the Task Scheduling System (TSS). In the user module, the process time of each task is in accordance with a general distribution. In the task scheduling module, we take a weighted sum of makespan and flowtime as the objective function and use an Ant Colony Optimization (ACO) and a Genetic Algorithm (GA) to solve the problem of cloud task scheduling. Simulation results show that the convergence speed and output performance of our Genetic Algorithm-Chaos Ant Colony Optimization (GA-CACO) are optimal.http://dx.doi.org/10.1155/2017/2503153
collection DOAJ
language English
format Article
sources DOAJ
author Hongyan Cui
Xiaofei Liu
Tao Yu
Honggang Zhang
Yajun Fang
Zongguo Xia
spellingShingle Hongyan Cui
Xiaofei Liu
Tao Yu
Honggang Zhang
Yajun Fang
Zongguo Xia
Cloud Service Scheduling Algorithm Research and Optimization
Security and Communication Networks
author_facet Hongyan Cui
Xiaofei Liu
Tao Yu
Honggang Zhang
Yajun Fang
Zongguo Xia
author_sort Hongyan Cui
title Cloud Service Scheduling Algorithm Research and Optimization
title_short Cloud Service Scheduling Algorithm Research and Optimization
title_full Cloud Service Scheduling Algorithm Research and Optimization
title_fullStr Cloud Service Scheduling Algorithm Research and Optimization
title_full_unstemmed Cloud Service Scheduling Algorithm Research and Optimization
title_sort cloud service scheduling algorithm research and optimization
publisher Hindawi-Wiley
series Security and Communication Networks
issn 1939-0114
1939-0122
publishDate 2017-01-01
description We propose a cloud service scheduling model that is referred to as the Task Scheduling System (TSS). In the user module, the process time of each task is in accordance with a general distribution. In the task scheduling module, we take a weighted sum of makespan and flowtime as the objective function and use an Ant Colony Optimization (ACO) and a Genetic Algorithm (GA) to solve the problem of cloud task scheduling. Simulation results show that the convergence speed and output performance of our Genetic Algorithm-Chaos Ant Colony Optimization (GA-CACO) are optimal.
url http://dx.doi.org/10.1155/2017/2503153
work_keys_str_mv AT hongyancui cloudserviceschedulingalgorithmresearchandoptimization
AT xiaofeiliu cloudserviceschedulingalgorithmresearchandoptimization
AT taoyu cloudserviceschedulingalgorithmresearchandoptimization
AT honggangzhang cloudserviceschedulingalgorithmresearchandoptimization
AT yajunfang cloudserviceschedulingalgorithmresearchandoptimization
AT zongguoxia cloudserviceschedulingalgorithmresearchandoptimization
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