Efficient resource optimization and scheduling of QoS in cloud content delivery network

Shah, Ateet Jayeshkumar (2018) Efficient resource optimization and scheduling of QoS in cloud content delivery network. Masters thesis, Dublin, National College of Ireland.

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Abstract

Cloud computing offers infrastructure platform which enables users to host different services in cloud. The benefits of virtualization, distributed nature of cloud and the scalability feature of cloud can be leveraged in content delivery network (CDN) which forms cloud content delivery network. CDN in cloud has become one of the significant services of the internet due to growing internet traffic. Server-side processing, streaming of content and delivering the content with better quality of service (QoS) at reduced cost is a key issue for content providers and end users. Many times, there is an uncertainty of delivering the content and achieving guaranteed quality of service (latency issue, real time issue, response and execution time issue) since the demand from the end user is dynamic. Thus, achieving guarantee quality of service becomes our primary objective in cloud content delivery network and forms the basis of our research. We propose an improved method on dynamic rate scheduling to improve QoS in cloud content delivery network. We are performing the experiment on cloud sim toolkit to create a distributed content delivery network environment and comparing it with different techniques like load balance and static mechanism. This research proposal is aimed towards the open problem of quality of service in cloud computing environment for content delivery network. This work is dedicated to researchers in cloud domain, content delivery network and for academic students.
Keywords – Cloud computing, Content delivery network, dynamic rate scheduling, quality of service

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software T Technology > T Technology (General) > Information Technology > Cloud computing
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Dan English
Date Deposited:	03 Jun 2020 15:53
Last Modified:	03 Jun 2020 15:53
URI:	https://norma.ncirl.ie/id/eprint/4231

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