Scheduling Method of Data-Intensive Applications in Cloud Computing Environments

The virtualization of cloud computing improves the utilization of resources and energy. And a cloud user can deploy his/her own applications and related data on a pay-as-you-go basis. The communications between an application and a data storage node, as well as within the application, have a great i...

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Main Authors: Xiong Fu, Yeliang Cang, Xinxin Zhu, Song Deng
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/605439
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spelling doaj-2df3094f90b14423b31bfa6bd9d811b22020-11-24T20:51:46ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/605439605439Scheduling Method of Data-Intensive Applications in Cloud Computing EnvironmentsXiong Fu0Yeliang Cang1Xinxin Zhu2Song Deng3School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, ChinaSchool of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, ChinaSchool of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, ChinaInstitute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, ChinaThe virtualization of cloud computing improves the utilization of resources and energy. And a cloud user can deploy his/her own applications and related data on a pay-as-you-go basis. The communications between an application and a data storage node, as well as within the application, have a great impact on the execution efficiency of the application. The locations of subtasks of an application and the data that transferred between the subtasks are the main reason why communication delay exists. The communication delay can affect the completion time of the application. In this paper, we take into account the data transmission time and communications between subtasks and propose a heuristic optimal virtual machine (VM) placement algorithm. Related simulations demonstrate that this algorithm can reduce the completion time of user tasks and ensure the feasibility and effectiveness of the overall network performance of applications when running in a cloud computing environment.http://dx.doi.org/10.1155/2015/605439
collection DOAJ
language English
format Article
sources DOAJ
author Xiong Fu
Yeliang Cang
Xinxin Zhu
Song Deng
spellingShingle Xiong Fu
Yeliang Cang
Xinxin Zhu
Song Deng
Scheduling Method of Data-Intensive Applications in Cloud Computing Environments
Mathematical Problems in Engineering
author_facet Xiong Fu
Yeliang Cang
Xinxin Zhu
Song Deng
author_sort Xiong Fu
title Scheduling Method of Data-Intensive Applications in Cloud Computing Environments
title_short Scheduling Method of Data-Intensive Applications in Cloud Computing Environments
title_full Scheduling Method of Data-Intensive Applications in Cloud Computing Environments
title_fullStr Scheduling Method of Data-Intensive Applications in Cloud Computing Environments
title_full_unstemmed Scheduling Method of Data-Intensive Applications in Cloud Computing Environments
title_sort scheduling method of data-intensive applications in cloud computing environments
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description The virtualization of cloud computing improves the utilization of resources and energy. And a cloud user can deploy his/her own applications and related data on a pay-as-you-go basis. The communications between an application and a data storage node, as well as within the application, have a great impact on the execution efficiency of the application. The locations of subtasks of an application and the data that transferred between the subtasks are the main reason why communication delay exists. The communication delay can affect the completion time of the application. In this paper, we take into account the data transmission time and communications between subtasks and propose a heuristic optimal virtual machine (VM) placement algorithm. Related simulations demonstrate that this algorithm can reduce the completion time of user tasks and ensure the feasibility and effectiveness of the overall network performance of applications when running in a cloud computing environment.
url http://dx.doi.org/10.1155/2015/605439
work_keys_str_mv AT xiongfu schedulingmethodofdataintensiveapplicationsincloudcomputingenvironments
AT yeliangcang schedulingmethodofdataintensiveapplicationsincloudcomputingenvironments
AT xinxinzhu schedulingmethodofdataintensiveapplicationsincloudcomputingenvironments
AT songdeng schedulingmethodofdataintensiveapplicationsincloudcomputingenvironments
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