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Integration and Optimization of British and American Literature Information Resources in the Distributed Cloud Computing Environment.
- Source :
-
Computational intelligence and neuroscience [Comput Intell Neurosci] 2022 Jun 07; Vol. 2022, pp. 4318962. Date of Electronic Publication: 2022 Jun 07 (Print Publication: 2022). - Publication Year :
- 2022
-
Abstract
- One of the most effective approaches to improve resource usage efficiency and degree of resource collecting is to integrate resources. Many studies on the integration of information resources are also available. The search engines are the most well-known. At the same time, this article intends to optimize the integration of British and American literature information resources by employing distributed cloud computing, based on the needs of British and American literature. This research develops a model for the dispersed nature of cloud computing. It optimizes the method by fitting the mathematical model of transmission cost and latency. This article analyzes the weaknesses of the current British and American literature information resource integration and optimizes them for the integration of British and American literature resources. The Random algorithm has the longest delay, according to the results of this paper's experiments (maximum user weighted distance). The algorithms NPA-PDP and BWF have longer delays than the algorithm Opt. The percentage decline varies between 0.17 percent and 1.11 percent for different algorithms. It demonstrates that the algorithm presented in this work can be used to integrate and maximize information resources from English and American literature.<br />Competing Interests: The author does not have any possible conflicts of interest.<br /> (Copyright © 2022 Mei Chen.)
- Subjects :
- Models, Theoretical
Publications
United States
Algorithms
Cloud Computing
Subjects
Details
- Language :
- English
- ISSN :
- 1687-5273
- Volume :
- 2022
- Database :
- MEDLINE
- Journal :
- Computational intelligence and neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- 35712065
- Full Text :
- https://doi.org/10.1155/2022/4318962