Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/253262
Title: | An optimized multi objective QOS aware and security aware task scheduling in cloud computing environment |
Researcher: | Roshni Thanka M |
Guide(s): | Uma Maheswari P |
Keywords: | Cloud Computing Engineering and Technology,Computer Science,Computer Science Interdisciplinary Applications Optimized Multi Objective QoS Aware |
University: | Anna University |
Completed Date: | 2018 |
Abstract: | Cloud computing is a huge scalable distributed environment where the cloud resources are virtualized to meet the computing needs of cloud end users through the internet. It provides a larger pool of resources such as physical services, networking capabilities, storage for the user as a greatly flexible configuration model, significantly reduced risk model, and pay-peruse utility computing method to reduce the burden of understanding, protecting, and managing the underlying infrastructures. The cloud characteristics such as on-demand service, ubiquitous nature, pay-per-use, elasticity, location independent resource sharing enables the cloud user to achieve their business goals through the various services of cloud computing such as Software as a Service, Platform as a Service and Infrastructure as a Service. The ultimate aim of cloud service providers is to improve the resource utilization and to gain maximum profit. The cloud provides its resources as services based on the current demand of the cloud users. Managing these resources is a vital role of cloud environment. The attracting features of cloud computing increase the cloud users to run their scientific and complex application which may require parallel processing for completing their jobs efficiently. In these scenarios if the users submitted jobs are not properly scheduled to its right resources lead to poor performance. The very essential scheduling parameters to be considered while scheduling are makespan, completion time, processing time, bandwidth, cost, security, job migration, resource utilization, energy consumption, quality of service, and performance. The productivity and performance of cloud services always depend upon the performance of the user submitted task to the cloud environment. newline |
Pagination: | xx, 131p. |
URI: | http://hdl.handle.net/10603/253262 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 303.13 kB | Adobe PDF | View/Open |
02_certificates.pdf | 1.23 MB | Adobe PDF | View/Open | |
03_abstract.pdf | 217.22 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 185.63 kB | Adobe PDF | View/Open | |
05_contents.pdf | 300.34 kB | Adobe PDF | View/Open | |
06_list_of_symbols and abbreviations.pdf | 310.84 kB | Adobe PDF | View/Open | |
07_chapter1.pdf | 790.98 kB | Adobe PDF | View/Open | |
08_chapter2.pdf | 660.49 kB | Adobe PDF | View/Open | |
09_chapter3.pdf | 580.97 kB | Adobe PDF | View/Open | |
10_chapter4.pdf | 934.51 kB | Adobe PDF | View/Open | |
11_chapter5.pdf | 695.45 kB | Adobe PDF | View/Open | |
12_conclusion.pdf | 366.33 kB | Adobe PDF | View/Open | |
13_references.pdf | 543.83 kB | Adobe PDF | View/Open | |
14_list_of_publications.pdf | 427.23 kB | Adobe PDF | View/Open |
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