Mathematical Assessment of CDN Servers in a Cloud Computing Environment: A Case of Big Data for e-Governance

Srivastava, R (2016) Mathematical Assessment of CDN Servers in a Cloud Computing Environment: A Case of Big Data for e-Governance. International Journal of Computer Applications, 141 (3). pp. 29-33. ISSN 0975-8887

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Abstract

Cloud computing environment delivers a countless tractability and accessibility of computing resources at a lesser price. This evolving technology unlocks an innovative eon of e-services provided by Government. However, as the number of users retrieving these e-services are cumulative, it is problematic for the current e-Government Infrastructure to accomplish these requirements. The exceptional way to succeed the problem is the employment and usage of CDN Servers. A CDN is a network of geographically distributed content delivery nodes that are settled for effectual delivery of digital content on behalf of content providers. The paper organizes the mathematical calculation to inspect the average response time for exploring the content from the e-Government Infrastructure implementing CDN Servers. There are three possible situations which are calculated in the research, as cited below:
When the request is available at the first CDN Server.
When the request is not available at the first CDN Server but at the other CDN Servers.
When the request is not available at any CDN Servers, but to be transferred to e-Government Cloud Computing Infrastructure.
This mechanism may best serve as a guideline to identify the best content server to respond to a request directed to the CDN Servers.

Affiliation: Skyline University College
SUC Author(s): Srivastava, R
All Author(s): Srivastava, R
Item Type: Article
Uncontrolled Keywords: CDN Servers, Hit Ratio, Miss Ratio, Average Response Time, Cloud Computing, e-Government Infrastructure.
Subjects: A Business and Management > AB Business and Management
Divisions: Skyline University College > School of Business
Depositing User: Mr SUC Library
Date Deposited: 08 Jun 2022 06:27
Last Modified: 08 Jun 2022 06:27
URI: https://research.skylineuniversity.ac.ae/id/eprint/373
Publisher URL:
Publisher OA policy: https://v2.sherpa.ac.uk/id/publication/25751
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