Enhance Cloudlet Scheduling Policy (ECSP) using cloudsim toolkit with resubmission fault tolerance mechanism
Several research works are still going on in the domain of cloud computing and many traditional methods are used to highlight the parameters involved in QoS (Quality of Services) of cloud. QoS is associated with several parameters used to guarantee a service level such as performance, availability,...
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my-upm-ir.690022019-06-19T03:09:25Z Enhance Cloudlet Scheduling Policy (ECSP) using cloudsim toolkit with resubmission fault tolerance mechanism 2018-01 Auzir, Juliza Several research works are still going on in the domain of cloud computing and many traditional methods are used to highlight the parameters involved in QoS (Quality of Services) of cloud. QoS is associated with several parameters used to guarantee a service level such as performance, availability, and reliability. In cloud computing, to ensure cloud services proficient in environment, one of the challenges is to provide efficient cloudlet scheduling policy. The cloudlet scheduling policy plays key role as a lead to improve overall system performance such as minimizing the turnaround time waiting time and context switching. This project emphasizes and evaluates the QoS parameter by performed result comparison with previous work – Improved Round Robin Cloudlet Scheduling Algorithm (IRRCSA) and Round Robin Algorithm (RRA). CloudSim Toolkit will be used to improved cloudlet scheduling algorithm as well as Qualtiy of Sevice (QoS) performance by providing better execution time and turnaround time. In addition, this project also will include fault tolerance function as extended from previous work. Cloud computing 2018-01 Thesis http://psasir.upm.edu.my/id/eprint/69002/ http://psasir.upm.edu.my/id/eprint/69002/1/FSKTM%202018%2045%20-%20IR.pdf text en public masters Universiti Putra Malaysia Cloud computing |
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Cloud computing Auzir, Juliza Enhance Cloudlet Scheduling Policy (ECSP) using cloudsim toolkit with resubmission fault tolerance mechanism |
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Several research works are still going on in the domain of cloud computing and many traditional methods are used to highlight the parameters involved in QoS (Quality of Services) of cloud. QoS is associated with several parameters used to guarantee a service level such as performance, availability, and reliability. In cloud computing, to ensure cloud services proficient in environment, one of the challenges is to provide efficient cloudlet scheduling policy. The cloudlet scheduling policy plays key role as a lead to improve overall system performance such as minimizing the turnaround time waiting time and context switching. This project emphasizes and evaluates the QoS parameter by performed result comparison with previous work – Improved Round Robin Cloudlet Scheduling Algorithm (IRRCSA) and Round Robin Algorithm (RRA). CloudSim Toolkit will be used to improved cloudlet scheduling algorithm as well as Qualtiy of Sevice (QoS) performance by providing better execution time and turnaround time. In addition, this project also will include fault tolerance function as extended from previous work. |
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Thesis |
qualification_level |
Master's degree |
author |
Auzir, Juliza |
author_facet |
Auzir, Juliza |
author_sort |
Auzir, Juliza |
title |
Enhance Cloudlet Scheduling Policy (ECSP) using cloudsim toolkit with resubmission fault tolerance mechanism |
title_short |
Enhance Cloudlet Scheduling Policy (ECSP) using cloudsim toolkit with resubmission fault tolerance mechanism |
title_full |
Enhance Cloudlet Scheduling Policy (ECSP) using cloudsim toolkit with resubmission fault tolerance mechanism |
title_fullStr |
Enhance Cloudlet Scheduling Policy (ECSP) using cloudsim toolkit with resubmission fault tolerance mechanism |
title_full_unstemmed |
Enhance Cloudlet Scheduling Policy (ECSP) using cloudsim toolkit with resubmission fault tolerance mechanism |
title_sort |
enhance cloudlet scheduling policy (ecsp) using cloudsim toolkit with resubmission fault tolerance mechanism |
granting_institution |
Universiti Putra Malaysia |
publishDate |
2018 |
url |
http://psasir.upm.edu.my/id/eprint/69002/1/FSKTM%202018%2045%20-%20IR.pdf |
_version_ |
1747812655739961344 |