Performance analysis on multi-attribute combinatorial double auction model for resource allocation in cloud computing

Cloud computing is a distinctive form of the recent well-developed distributed computing which supplies multiple services to the customers on their demand. Recently, the main concern of cloud computing is a typical resource management, especially in terms of resource allocation. Various number...

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Main Author: Mohamed El-Sherksi, Suad Abdalla
Format: Thesis
Language:English
Published: 2017
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Online Access:http://psasir.upm.edu.my/id/eprint/67856/1/FSKTM%202017%2020%20IR.pdf
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spelling my-upm-ir.678562019-03-28T07:07:12Z Performance analysis on multi-attribute combinatorial double auction model for resource allocation in cloud computing 2017-01 Mohamed El-Sherksi, Suad Abdalla Cloud computing is a distinctive form of the recent well-developed distributed computing which supplies multiple services to the customers on their demand. Recently, the main concern of cloud computing is a typical resource management, especially in terms of resource allocation. Various number of methods were and still being proposed by researchers in order to provide sufficient solutions that overcome the issues of current resource allocation methods. In this work, a performance analysis is conducted on a dynamic market based algorithm for resource allocation in virtual machines of the cloud. For multi-attribute combinatorial double auction model where the simulation experiments was performed to simulate the actual business auctions’ procedures in order to consider the profits for both the cloud customers and providers, manage the QoS metrics that being provided to cloud customers, and apply penalties on false QoS providers as well as compensating the customers. The results showed that multi-attribute combinatorial double auction model has enhanced the previous combinatorial double auction resource allocation model by including QoS in provider’s bids, prevented SLA violation by penalty imposition and guaranteed customers’ satisfaction with delivered service. And for further analysis two more parameters were measured which are execution time and VMs’ utilization was improved. Cloud computing 2017-01 Thesis http://psasir.upm.edu.my/id/eprint/67856/ http://psasir.upm.edu.my/id/eprint/67856/1/FSKTM%202017%2020%20IR.pdf text en public masters Universiti Putra Malaysia Cloud computing
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
topic Cloud computing


spellingShingle Cloud computing


Mohamed El-Sherksi, Suad Abdalla
Performance analysis on multi-attribute combinatorial double auction model for resource allocation in cloud computing
description Cloud computing is a distinctive form of the recent well-developed distributed computing which supplies multiple services to the customers on their demand. Recently, the main concern of cloud computing is a typical resource management, especially in terms of resource allocation. Various number of methods were and still being proposed by researchers in order to provide sufficient solutions that overcome the issues of current resource allocation methods. In this work, a performance analysis is conducted on a dynamic market based algorithm for resource allocation in virtual machines of the cloud. For multi-attribute combinatorial double auction model where the simulation experiments was performed to simulate the actual business auctions’ procedures in order to consider the profits for both the cloud customers and providers, manage the QoS metrics that being provided to cloud customers, and apply penalties on false QoS providers as well as compensating the customers. The results showed that multi-attribute combinatorial double auction model has enhanced the previous combinatorial double auction resource allocation model by including QoS in provider’s bids, prevented SLA violation by penalty imposition and guaranteed customers’ satisfaction with delivered service. And for further analysis two more parameters were measured which are execution time and VMs’ utilization was improved.
format Thesis
qualification_level Master's degree
author Mohamed El-Sherksi, Suad Abdalla
author_facet Mohamed El-Sherksi, Suad Abdalla
author_sort Mohamed El-Sherksi, Suad Abdalla
title Performance analysis on multi-attribute combinatorial double auction model for resource allocation in cloud computing
title_short Performance analysis on multi-attribute combinatorial double auction model for resource allocation in cloud computing
title_full Performance analysis on multi-attribute combinatorial double auction model for resource allocation in cloud computing
title_fullStr Performance analysis on multi-attribute combinatorial double auction model for resource allocation in cloud computing
title_full_unstemmed Performance analysis on multi-attribute combinatorial double auction model for resource allocation in cloud computing
title_sort performance analysis on multi-attribute combinatorial double auction model for resource allocation in cloud computing
granting_institution Universiti Putra Malaysia
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/67856/1/FSKTM%202017%2020%20IR.pdf
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