Abstract
This study is focusing on improving the availability of federated storage services in order to provide better quality-of-service (QoS) to the customer with the minimum use of resources. One of the most efficient solutions to get the best experience in the cloud is to combine the services offered. In order for this to happen, there exist different approaches for selecting the best subset of services to reach the optimal performance. However, those works focus on one time selection processes, despite of customer's requirements are continuously changing and demanding adaptable storage service. In this research, I propose a method to improve storage availability through log sentiment analysis and intelligent replication. This methodology is based on the merging of two types of log analysis and the measurement of availability and performance metrics in order to select the best subset of services in cloud storage service federation.
| Original language | English |
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| Title of host publication | Proceedings of 2017 International Conference on Machine Learning and Soft Computing, ICMLSC 2017 |
| Publisher | Association for Computing Machinery |
| Pages | 148-153 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781450348287 |
| DOIs | |
| Publication status | Published - 13 Jan 2017 |
| Event | 2017 International Conference on Machine Learning and Soft Computing, ICMLSC 2017 - Ho Chi Minh City, Viet Nam Duration: 13 Jan 2017 → 16 Jan 2017 |
Publication series
| Name | ACM International Conference Proceeding Series |
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Conference
| Conference | 2017 International Conference on Machine Learning and Soft Computing, ICMLSC 2017 |
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| Country/Territory | Viet Nam |
| City | Ho Chi Minh City |
| Period | 13/01/17 → 16/01/17 |
Bibliographical note
Publisher Copyright:© 2017 ACM.
Keywords
- Availability
- Cloud computing
- Federated Cloud Storage
- Log analysis
- Performance
- Replication
- Sentiment analysis
- Subset selection