Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/218626
Title: | A MongoDB based Performance Optimization Framework for Big Data in Cloud Environments |
Researcher: | Revina Rebecca D |
Guide(s): | Elizabeth Shanthi I |
Keywords: | Cloud computing Big Data MongoDB |
University: | Avinashilingam Deemed University For Women |
Completed Date: | 10/08/2018 |
Abstract: | Healthcare industry accumulates huge volumes of digital information day by day which are of newlinedifferent types and complex that is categorized as Big Data. The insights and knowledge gained from newlineBig Data adds value through Big Data Analytics (BDA). Cost minimization which is vital in BDA can newlinebe achieved by monitoring the system performance in the cloud. As the traditional methods of data newlinemanagement do not fit to the cloud, it was needed to look for a NoSQL based solution and to optimize newlinethe performance through minimal infrastructural need in the cloud environment. Hence there is a need newlineto develop a Performance Optimization Framework for the NoSQL database under consideration. The newlinemain objective is to study the performance of the NoSQL database. Here the Document data model newlineMongoDB in Cloud environments is considered as it showed better performance than its counterparts. newlineInfrastructure optimization was achieved through series of practical decisive experiments, which newlineresulted into a number of highly useful findings. Based on those findings, it was possible to formulate newlinethe MongoDB based Optimized Resource provisioning method. This has two Modules i) the optimized newlineperformance enhancement representation ii) Optimized Resource provisioning algorithm. These two newlinemodules perform the needed infrastructure optimization with Cost minimization as expected. This can newlinewell be incorporated to develop a MongoDB based performance Optimization Framework suggested. newlinei) Major objectives : newlineo Methods to efficiently handle unstructured Medical images. newlineo Methods to efficiently archive and handle huge volume/Sized Images newlineo Methods to share huge Sized Medical Images newlineo Methods for Performance Optimization newlineHypothesis: To design the essential components for a NoSQL based Performance Optimization newlineFramework for Big-Data in Cloud Environments. newlineii) Methodology : newlineand#61620; Find the Suitable NoSQL database to store and Analyze Big data newlineand#61620; A performance metrics-based study on the selected NoSQL is to be done. newlineand#61620; Analyze the Results- Record the inferences. |
Pagination: | 166 p. |
URI: | http://hdl.handle.net/10603/218626 |
Appears in Departments: | Department of Computer Science |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 97.24 kB | Adobe PDF | View/Open |
02_certificate.pdf | 261.41 kB | Adobe PDF | View/Open | |
03_acknowledgement.pdf | 102.78 kB | Adobe PDF | View/Open | |
04_content.pdf | 119.8 kB | Adobe PDF | View/Open | |
05_list of table and figures.pdf | 109.46 kB | Adobe PDF | View/Open | |
06_chapter 1.pdf | 916.75 kB | Adobe PDF | View/Open | |
07_chapter 2.pdf | 813.34 kB | Adobe PDF | View/Open | |
08_chapter 3.pdf | 805.75 kB | Adobe PDF | View/Open | |
09_chapter 4.pdf | 1.1 MB | Adobe PDF | View/Open | |
10_chapter 5.pdf | 926.19 kB | Adobe PDF | View/Open | |
11_chapter 6.pdf | 996.58 kB | Adobe PDF | View/Open | |
12_chapter 7.pdf | 841.3 kB | Adobe PDF | View/Open | |
13_chapter 8.pdf | 799.19 kB | Adobe PDF | View/Open | |
14_chapter 9.pdf | 795.55 kB | Adobe PDF | View/Open | |
15_references.pdf | 799.22 kB | Adobe PDF | View/Open |
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