Data Replication-Based Scheduling in Cloud Computing Environment
Abstract— High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable and elastic platform. Furthermore, ac...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Science and Research Branch,Islamic Azad University
2017-05-01
|
| Series: | Journal of Advances in Computer Engineering and Technology |
| Subjects: | |
| Online Access: | http://jacet.srbiau.ac.ir/article_10044_aef87f426061ec5032e3f0953e9d4136.pdf |
| _version_ | 1811304942174994432 |
|---|---|
| author | Bahareh Rahmati Amir Masoud Rahmani Ali Rezaei |
| author_facet | Bahareh Rahmati Amir Masoud Rahmani Ali Rezaei |
| author_sort | Bahareh Rahmati |
| collection | DOAJ |
| description | Abstract— High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable and elastic platform. Furthermore, accessing data files is critical for performing such applications. Sometimes accessing data becomes a bottleneck for the whole cloud workflow system and decreases the performance of the system dramatically. Job scheduling and data replication are two important techniques which can enhance the performance of data-intensive applications. It is wise to integrate these techniques into one framework for achieving a single objective. In this paper, we integrate data replication and job scheduling with the aim of reducing response time by reduction of data access time in cloud computing environment. This is called data replication-based scheduling (DRBS). Simulation results show the effectiveness of our algorithm in comparison with well-known algorithms such as random and round-robin. |
| first_indexed | 2024-04-13T08:16:28Z |
| format | Article |
| id | doaj.art-0685c8abde8d4e95b364a5f20247c721 |
| institution | Directory Open Access Journal |
| issn | 2423-4192 2423-4206 |
| language | English |
| last_indexed | 2024-04-13T08:16:28Z |
| publishDate | 2017-05-01 |
| publisher | Science and Research Branch,Islamic Azad University |
| record_format | Article |
| series | Journal of Advances in Computer Engineering and Technology |
| spelling | doaj.art-0685c8abde8d4e95b364a5f20247c7212022-12-22T02:54:46ZengScience and Research Branch,Islamic Azad UniversityJournal of Advances in Computer Engineering and Technology2423-41922423-42062017-05-0132758010044Data Replication-Based Scheduling in Cloud Computing EnvironmentBahareh Rahmati0Amir Masoud Rahmani1Ali Rezaei2Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranAbstract— High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable and elastic platform. Furthermore, accessing data files is critical for performing such applications. Sometimes accessing data becomes a bottleneck for the whole cloud workflow system and decreases the performance of the system dramatically. Job scheduling and data replication are two important techniques which can enhance the performance of data-intensive applications. It is wise to integrate these techniques into one framework for achieving a single objective. In this paper, we integrate data replication and job scheduling with the aim of reducing response time by reduction of data access time in cloud computing environment. This is called data replication-based scheduling (DRBS). Simulation results show the effectiveness of our algorithm in comparison with well-known algorithms such as random and round-robin.http://jacet.srbiau.ac.ir/article_10044_aef87f426061ec5032e3f0953e9d4136.pdfIndex Terms— Cloud ComputingData Access TimeData ReplicationJob SchedulingResponse Time |
| spellingShingle | Bahareh Rahmati Amir Masoud Rahmani Ali Rezaei Data Replication-Based Scheduling in Cloud Computing Environment Journal of Advances in Computer Engineering and Technology Index Terms— Cloud Computing Data Access Time Data Replication Job Scheduling Response Time |
| title | Data Replication-Based Scheduling in Cloud Computing Environment |
| title_full | Data Replication-Based Scheduling in Cloud Computing Environment |
| title_fullStr | Data Replication-Based Scheduling in Cloud Computing Environment |
| title_full_unstemmed | Data Replication-Based Scheduling in Cloud Computing Environment |
| title_short | Data Replication-Based Scheduling in Cloud Computing Environment |
| title_sort | data replication based scheduling in cloud computing environment |
| topic | Index Terms— Cloud Computing Data Access Time Data Replication Job Scheduling Response Time |
| url | http://jacet.srbiau.ac.ir/article_10044_aef87f426061ec5032e3f0953e9d4136.pdf |
| work_keys_str_mv | AT baharehrahmati datareplicationbasedschedulingincloudcomputingenvironment AT amirmasoudrahmani datareplicationbasedschedulingincloudcomputingenvironment AT alirezaei datareplicationbasedschedulingincloudcomputingenvironment |