Adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing
Cloud computing is growing fast and spreading more into an aspect of our life. Apart from traditional web services such as searching, webmail and online education, many organizations, enterprise, personal developers and even individuals could make use of Cloud computing services. Healthcare communit...
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| Format: | Thesis |
| Language: | English |
| Published: |
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/82952/ http://psasir.upm.edu.my/id/eprint/82952/1/FSKTM%202019%2037%20IR.pdf |
| _version_ | 1848859401662758912 |
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| author | Muhammad, Aliyu |
| author_facet | Muhammad, Aliyu |
| author_sort | Muhammad, Aliyu |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Cloud computing is growing fast and spreading more into an aspect of our life. Apart from traditional web services such as searching, webmail and online education, many organizations, enterprise, personal developers and even individuals could make use of Cloud computing services. Healthcare community services are one of the vital aspects of our life. The volume of data the healthcare industries has to collect and manage are growing rapidly over the past decade. The Cloud infrastructure is helping healthcare organizations use large volumes of collected data to be effectively and efficiently managed, also to develop better clinical responses. Single Cloud Data Centers have a limitation of physical resources, thus, leveraging cloud confederation is a good approach to solve the limitation problems, but issues arise when it comes to selection for optimal CDC among the confederated CDC to complete a task. In this work, adaptive and fault-tolerant scheduling approach for securing healthcare information is developed for a multi-Cloud Environment, where we use fuzzy logic for selection decision and square matrix multiplication for predictions of healthy/unhealthy resources. Cloudsim is used for the simulation system of our FT-FnF model and shows a better result in regards to users Qos, Providers profit, and resource utilization compared to the FnF model. |
| first_indexed | 2025-11-15T12:28:45Z |
| format | Thesis |
| id | upm-82952 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:28:45Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-829522020-07-24T02:24:52Z http://psasir.upm.edu.my/id/eprint/82952/ Adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing Muhammad, Aliyu Cloud computing is growing fast and spreading more into an aspect of our life. Apart from traditional web services such as searching, webmail and online education, many organizations, enterprise, personal developers and even individuals could make use of Cloud computing services. Healthcare community services are one of the vital aspects of our life. The volume of data the healthcare industries has to collect and manage are growing rapidly over the past decade. The Cloud infrastructure is helping healthcare organizations use large volumes of collected data to be effectively and efficiently managed, also to develop better clinical responses. Single Cloud Data Centers have a limitation of physical resources, thus, leveraging cloud confederation is a good approach to solve the limitation problems, but issues arise when it comes to selection for optimal CDC among the confederated CDC to complete a task. In this work, adaptive and fault-tolerant scheduling approach for securing healthcare information is developed for a multi-Cloud Environment, where we use fuzzy logic for selection decision and square matrix multiplication for predictions of healthy/unhealthy resources. Cloudsim is used for the simulation system of our FT-FnF model and shows a better result in regards to users Qos, Providers profit, and resource utilization compared to the FnF model. 2019-06 Thesis NonPeerReviewed text en http://psasir.upm.edu.my/id/eprint/82952/1/FSKTM%202019%2037%20IR.pdf Muhammad, Aliyu (2019) Adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing. Masters thesis, Universiti Putra Malaysia. Cloud computing Information storage and retrieval systems Community health services |
| spellingShingle | Cloud computing Information storage and retrieval systems Community health services Muhammad, Aliyu Adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing |
| title | Adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing |
| title_full | Adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing |
| title_fullStr | Adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing |
| title_full_unstemmed | Adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing |
| title_short | Adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing |
| title_sort | adaptive and fault-tolerant scheduling for effective data storing in healthcare community using cloud computing |
| topic | Cloud computing Information storage and retrieval systems Community health services |
| url | http://psasir.upm.edu.my/id/eprint/82952/ http://psasir.upm.edu.my/id/eprint/82952/1/FSKTM%202019%2037%20IR.pdf |