Optimization of Big Data Scheduling in Social Networks
In social network big data scheduling, it is easy for target data to conflict in the same data node. Of the different kinds of entropy measures, this paper focuses on the optimization of target entropy. Therefore, this paper presents an optimized method for the scheduling of big data in social netwo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-09-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/21/9/902 |
| _version_ | 1798040619460853760 |
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| author | Weina Fu Shuai Liu Gautam Srivastava |
| author_facet | Weina Fu Shuai Liu Gautam Srivastava |
| author_sort | Weina Fu |
| collection | DOAJ |
| description | In social network big data scheduling, it is easy for target data to conflict in the same data node. Of the different kinds of entropy measures, this paper focuses on the optimization of target entropy. Therefore, this paper presents an optimized method for the scheduling of big data in social networks and also takes into account each task’s amount of data communication during target data transmission to construct a big data scheduling model. Firstly, the task scheduling model is constructed to solve the problem of conflicting target data in the same data node. Next, the necessary conditions for the scheduling of tasks are analyzed. Then, the a periodic task distribution function is calculated. Finally, tasks are scheduled based on the minimum product of the corresponding resource level and the minimum execution time of each task is calculated. Experimental results show that our optimized scheduling model quickly optimizes the scheduling of social network data and solves the problem of strong data collision. |
| first_indexed | 2024-04-11T22:10:12Z |
| format | Article |
| id | doaj.art-9da3ca4d6c3741b1bde4e6f5a0ce9903 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-11T22:10:12Z |
| publishDate | 2019-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-9da3ca4d6c3741b1bde4e6f5a0ce99032022-12-22T04:00:35ZengMDPI AGEntropy1099-43002019-09-0121990210.3390/e21090902e21090902Optimization of Big Data Scheduling in Social NetworksWeina Fu0Shuai Liu1Gautam Srivastava2College of Information Science and Engineering, Hunan Normal University, Changsha 410081, ChinaCollege of Information Science and Engineering, Hunan Normal University, Changsha 410081, ChinaDepartment of Mathematics and Computer Science, Brandon University, Brandon, MB R7A 6A9, CanadaIn social network big data scheduling, it is easy for target data to conflict in the same data node. Of the different kinds of entropy measures, this paper focuses on the optimization of target entropy. Therefore, this paper presents an optimized method for the scheduling of big data in social networks and also takes into account each task’s amount of data communication during target data transmission to construct a big data scheduling model. Firstly, the task scheduling model is constructed to solve the problem of conflicting target data in the same data node. Next, the necessary conditions for the scheduling of tasks are analyzed. Then, the a periodic task distribution function is calculated. Finally, tasks are scheduled based on the minimum product of the corresponding resource level and the minimum execution time of each task is calculated. Experimental results show that our optimized scheduling model quickly optimizes the scheduling of social network data and solves the problem of strong data collision.https://www.mdpi.com/1099-4300/21/9/902big datadatabase designentropyinformation transfersocial networksinformation securityschedulingtask volumeclassificationoptimization |
| spellingShingle | Weina Fu Shuai Liu Gautam Srivastava Optimization of Big Data Scheduling in Social Networks Entropy big data database design entropy information transfer social networks information security scheduling task volume classification optimization |
| title | Optimization of Big Data Scheduling in Social Networks |
| title_full | Optimization of Big Data Scheduling in Social Networks |
| title_fullStr | Optimization of Big Data Scheduling in Social Networks |
| title_full_unstemmed | Optimization of Big Data Scheduling in Social Networks |
| title_short | Optimization of Big Data Scheduling in Social Networks |
| title_sort | optimization of big data scheduling in social networks |
| topic | big data database design entropy information transfer social networks information security scheduling task volume classification optimization |
| url | https://www.mdpi.com/1099-4300/21/9/902 |
| work_keys_str_mv | AT weinafu optimizationofbigdataschedulinginsocialnetworks AT shuailiu optimizationofbigdataschedulinginsocialnetworks AT gautamsrivastava optimizationofbigdataschedulinginsocialnetworks |