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
Subjects:	Cloud computing
Online Access:	http://psasir.upm.edu.my/id/eprint/67856/1/FSKTM%202017%2020%20IR.pdf
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id	my-upm-ir.67856
record_format	uketd_dc
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
_version_	1747812527439347712

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

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