Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/423415
Title: | Design and Development of Efficient Multi Core Aware Virtual Machine Placement Algorithms for Cloud Data Centers |
Researcher: | Nagadevi, S |
Guide(s): | Kasmir Raja, S V |
Keywords: | Computer Science Computer Science Software Engineering Engineering and Technology |
University: | SRM Institute of Science and Technology |
Completed Date: | 2022 |
Abstract: | One of the key challenges in a cloud data center is how do we place virtual machines on physical machines. Mapping virtual machines onto physical machines is known as virtual machine placement. The optimal virtual machine placement improves resource utilization and power consumption. The parameters such as resource wastage, overloaded physical machines and number of active physical machines are improved by properly mapping the virtual machines. The improper mapping between virtual machines and physical machines increases the overloaded and under-loaded physical machines and virtual machine migration. Since the resources are not properly used, more number of active physical machines are put into service. Therefore, physical machine consolidation techniques are needed to rearrange the virtual machines from overloaded and under-loaded physical machines. newlineTo place a virtual machine on a physical machine, various resource constraints are checked to see whether the physical machine is having the resource capacity demanded by the virtual machine or not. If the physical machine is not having sufficient resource capacity, then the next physical machine is checked. In most of the existing research works on virtual machine placement algorithms, the resource demands of the virtual machines are compared against the total resource capacity of physical machines newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/423415 |
Appears in Departments: | Department of Computer Science Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 172.65 kB | Adobe PDF | View/Open |
02_preliminary page.pdf | 453.55 kB | Adobe PDF | View/Open | |
03_content.pdf | 264.21 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 152.3 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 538.01 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 293.36 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 1.13 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 875.43 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 744.47 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 628.15 kB | Adobe PDF | View/Open | |
11_chapter 7.pdf | 158.4 kB | Adobe PDF | View/Open | |
12_annexures.pdf | 606.96 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 197.46 kB | Adobe PDF | View/Open |
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