RESOURCE SHARING TECHNOLOGY OF CLOUD COMPUTING
Hu, Zhehao (2016)
Hu, Zhehao
Centria-ammattikorkeakoulu
2016
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2016112417098
https://urn.fi/URN:NBN:fi:amk-2016112417098
Tiivistelmä
Development of computer science and technology, application of network education has become more mature. The technology of network learning resource sharing has been promoted by computers. It is significant promote the development of cloud computing education. Aiming at the need of education resource sharing, combined with the cloud computing service model, infrastructure and key technology. This thesis set up the educational resources sharing system to provide high quality sharing resources for users.
Cloud computing is an emerging shared infrastructure through virtualization technology in a large number of available network resources to form a virtual resource pool, automatic software implementation by management. Their cross-regional, cross-database resource integration capabilities break the scattered data resources to bring the information is not balanced, effective flow of resources and improve utilization; For cloud nodes can be easily added and removed and increase the size of the expansion resources to solve problems. Meanwhile, the data in the cloud uses distributed storage, capable of storing and accessing to share pressures, thereby improving system performance. Cloud resources take a pay model. In this way, the user can customize the resources of independent interest and promote personalized learning.
Cloud computing is an emerging shared infrastructure through virtualization technology in a large number of available network resources to form a virtual resource pool, automatic software implementation by management. Their cross-regional, cross-database resource integration capabilities break the scattered data resources to bring the information is not balanced, effective flow of resources and improve utilization; For cloud nodes can be easily added and removed and increase the size of the expansion resources to solve problems. Meanwhile, the data in the cloud uses distributed storage, capable of storing and accessing to share pressures, thereby improving system performance. Cloud resources take a pay model. In this way, the user can customize the resources of independent interest and promote personalized learning.