|Author's Email Address
||This thesis had been viewed 5355 times. Download 0 times.|
||Computer Science and Engineering|
|Type of Document
||The study of virtual machine deployment in cloud computing platform|
|Date of Defense
||Nowadays cloud-computing is the hottest topics in the study of Internet. Through internet connection, it provided calculation service and allowed both software/hardware resources sharing and virtualization resource-management. This service has provided brand-new service style and irreplaceable advantages. |
There are three types of cloud-computing service model: SaaS (Software as a Service), PaaS (Platform as a Service), IaaS (Infrastructure as a Service). Based on PaaS and researches of traditional virtual machine, the essay mainly discussed about issues of resource deployment and further designed a scheduling system with priority scheduling.
Practically, Docker Container and Swarm Cluster Management system are used as the technique basis and implementation of this essay are based on Distributed Docker Management System (DDMS). The aim of the essay is to improve its way for resource deployment: maximum the service numbers and conclude real-time factor in scheduling system. The new design is to authorize enough priority and hardware resources to the urgent request, and also satisfied the need of basic calculation service.
In the essay, we used Bin-Packing algorithm to solve resource-deployment problems. We not only discussed about different Bin-Packing algorithm but also provided the refinement method to equip with Bulk Arrivals functionality while at the same time achieving approximate efficiency of Online Bin-Packing and similar result of Offline Bin-Packing.
Finally, trying to testify each algorithm’s impact on cloud service system’s performance, we used queuing system to compared four different algorithms’ impact in our model and analyze each reference data and correlations to provide a scheduling system which aligned with the need of Cluster Deployment from developer’s viewpoint.
||Wei-Kuang Lai - chair|
Chien-Hsing Liu - co-chair
Hsiao-Guang Wu - co-chair
Cheng-Fou Chou - co-chair
Richard Lin - advisor
Indicate in-campus at 5 year and off-campus access at 5 year.|
|Date of Submission