| dc.contributor.author | Amoah, P. | |
| dc.date.accessioned | 2024-04-29T16:06:32Z | |
| dc.date.available | 2024-04-29T16:06:32Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | http://41.74.91.244:8080/handle/123456789/3431 | |
| dc.description | A dissertation in the Department of Information Technology Education, Faculty of Applied Sciences and Mathematics Education submitted to the School of Graduate Studies in Partial Fulfillment of the requirement for the award of the degree of Master of Science (Information Technology Education) in the University of Education, Winneba May, 2021 | en_US |
| dc.description.abstract | Cloud computing is an emerging technological breakthrough that offers a long-dreamed concept of computing as a service. The development of this modern technology in the IT domain has influenced almost all of the private and public sector organizations. Though cloud is implementing the dynamic and cost-effective model of on-demand operation, pay as you go, and assigning resources, security is often the area of concern in terms of its adoption. Moreover, due to the varying nature of the operation and implementation process, traditional in-depth security framework for defense cannot be implemented directly on cloud-based platform. However to safeguard the cloud-based infrastructure, the same principle of can be used. Many entities have used the disaster recovery method to promote continuity of operations. Disaster recovery mechanisms, however, require extensive personal intervention to restore the failed system and this cannot mitigate service outages because it may take longer following a network breakdown to get backup system fully functional. This dissertation proposed an automatic data recovery system that aims to achieve a robust, efficient, adaptable and effective recovery mechanism on a cloud-based system to help and support in this regard. First, a method was proposed to take advantage of cloud service and automatically restore from volatile network failure, without complicated manual operation. This improves service stability by offering a centralized self-organizing system, which can automatically recognize and restore failures. Then a model is proposed and extensively explained on the basis of the mechanism. Ultimately a test was deployed based on the concept to show the performance advantages of using this approach in cloud-based data recovery. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | University of Education, Winneba | en_US |
| dc.subject | Automated log based recovery algorithms | en_US |
| dc.subject | cloud computing | en_US |
| dc.title | Automated log based recovery algorithms used to recover lost data in cloud computing | en_US |
| dc.type | Thesis | en_US |