Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/509557
Title: | Studies on prediction of resource Contention in cloud and edge Computing architectures using Markov models |
Researcher: | Surya K |
Guide(s): | Maryanitarajam V |
Keywords: | Cloud Computer Science Computer Science Information Systems Computing architectures Engineering and Technology Markov models |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | Cloud computing provides an on-demand access of the services newlinehosted by the cloud provider through the internet. Cloud users can pay when newlinethe services are needed and disconnect when not needed. The effort of purchasing, newlineinstalling, configuring and managing resources becomes the responsibility newlineof the cloud service provider. The resources requested by the users should be newlineallocated as per the desired performance mentioned by the users in the Service newlineLevel Agreement (SLA). Hence, resource management across the cloud is of newlinesignificant importance in cloud computing. newlineEdge computing works jointly with the cloud to provide flexible solutions. newlineFor real-time applications that generate a large amount of data, edge newlinecomputing is the ideal solution. It provides real-time analytics where processing newlinetakes place closer to the asset, thereby reducing the reliance to the centralised newlinecloud. Even if the connectivity to the cloud cannot be made immediately, edge newlinecomputing enables processing and storage across the local network. At the same newlinetime, the cloud provides a centralized storage location for large-scale data analytics newline |
Pagination: | xviii,119p. |
URI: | http://hdl.handle.net/10603/509557 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 126.59 kB | Adobe PDF | View/Open |
02_prelimpage.pdf | 1.62 MB | Adobe PDF | View/Open | |
03_content.pdf | 107.46 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 63.71 kB | Adobe PDF | View/Open | |
05_chapter1.pdf | 168.31 kB | Adobe PDF | View/Open | |
06_chapter2.pdf | 127.51 kB | Adobe PDF | View/Open | |
07_chapter3.pdf | 1.11 MB | Adobe PDF | View/Open | |
08_chapter4.pdf | 507.84 kB | Adobe PDF | View/Open | |
09_chapter5.pdf | 295.29 kB | Adobe PDF | View/Open | |
10_annexure.pdf | 141.69 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 136.93 kB | Adobe PDF | View/Open |
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