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http://hdl.handle.net/10603/326272
Title: | Renewable Energy Based Efficient Framework for Sustainability of Data Centres |
Researcher: | Aujla, Gagangeet Singh |
Guide(s): | Kumar, Neeraj |
Keywords: | Cloud computing Data centers Renewable energy |
University: | Thapar Institute of Engineering and Technology |
Completed Date: | 2018 |
Abstract: | Cloud computing (CC) has emerged as one of the most powerful technologies from past few years in which end users can access various services as per their demands on pay per basis concept. The need for on-demand state-of-art services (smart sensing, e-healthcare and smart transportation) and computing infrastructure have paved way to the powerful paradigm of CC. These enhanced exible and reliable attributes o ered by the CC platform have led to its widespread popularity amongst the academia and industry. Using virtualization technology, cloud service providers (CSPs) create multiple copies of virtual resources deployed over a physical server to provide various services to the end users. Such a virtualized environment and resources are hosted on large geo-distributed, service-oriented and critical computing infrastructure known as data centers (DCs). Ever since its inception in 2000, CC paradigm has witnessed signi cant transitions in its overall usage, size, computational ability and underlying technology used for accessing various services. However, the huge amount of data generated by various smart devices such as-smart phones, tablets, smart meter, body sensors and wearable devices has escalated the load on DCs to a great extent. Moreover, with the emergence of Internet of things (IoT), the demand of real-time data storage, access and processing at cloud has increased manifold. In recent years, data-intensive applications such as{e-health, e-commerce and e-banking generate a huge volume of heterogeneous data which varies with respect to time and its location. Such a huge amount of data needs to be collected, stored, analyzed and processed e ectively using DC infrastructure. To handle such massive data streams generated from all these applications, existiii iv ing DCs infrastructure needs to be expanded both horizontally and vertically. The dependence of smart communities also make it critical to expand the DCs with millions of servers operating at geo-located sites. |
Pagination: | 225p. |
URI: | http://hdl.handle.net/10603/326272 |
Appears in Departments: | Department of Computer Science and Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 82.25 kB | Adobe PDF | View/Open |
02_certificate.pdf | 75.01 kB | Adobe PDF | View/Open | |
03_abstract.pdf | 81.22 kB | Adobe PDF | View/Open | |
04_acknowledgements.pdf | 55.48 kB | Adobe PDF | View/Open | |
05_contents.pdf | 89.3 kB | Adobe PDF | View/Open | |
06_list of figures.pdf | 137.92 kB | Adobe PDF | View/Open | |
07_list of tables.pdf | 71.25 kB | Adobe PDF | View/Open | |
08_list of important abbreviations.pdf | 70.01 kB | Adobe PDF | View/Open | |
09_chapter 1.pdf | 873.64 kB | Adobe PDF | View/Open | |
10_chpter 2.pdf | 383.43 kB | Adobe PDF | View/Open | |
11_chapter 3.pdf | 1.06 MB | Adobe PDF | View/Open | |
12_chapter 4.pdf | 2.51 MB | Adobe PDF | View/Open | |
13_chapter 5.pdf | 1.66 MB | Adobe PDF | View/Open | |
14_chapter 6.pdf | 1.46 MB | Adobe PDF | View/Open | |
15_chapter 7.pdf | 826.26 kB | Adobe PDF | View/Open | |
16_chapter 8.pdf | 106.38 kB | Adobe PDF | View/Open | |
17_bibliography.pdf | 146.08 kB | Adobe PDF | View/Open | |
18_list of publications.pdf | 93.3 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 120.67 kB | Adobe PDF | View/Open |
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