Optimizing Energy Consumption of Cloud Computing IaaS
A Master of Science thesis in Computer Engineering by Huda Ibrahim Mohamed entitled, "Optimizing Energy Consumption of Cloud Computing IaaS," submitted in May 2017. Thesis advisor is Dr. Raafat Aburukba and thesis co-advisor is Dr. Khaled El-Fakih. Soft and hard copy available.
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | doctoralThesis |
| منشور في: |
2017
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/11073/8909 |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
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| _version_ | 1864513431943512064 |
|---|---|
| author | Mohamed, Huda Ibrahim |
| author_facet | Mohamed, Huda Ibrahim |
| author_role | author |
| dc.contributor.none.fl_str_mv | Aburukba, Raafat El Fakih, Khaled |
| dc.creator.none.fl_str_mv | Mohamed, Huda Ibrahim |
| dc.date.none.fl_str_mv | 2017-09-11T08:32:12Z 2017-09-11T08:32:12Z 2017-05 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 35.232-2017.23 http://hdl.handle.net/11073/8909 |
| dc.language.none.fl_str_mv | en_US |
| dc.subject.none.fl_str_mv | Cloud computing task scheduling optimization integer linear programming power consumption genetic algorithms Cloud computing Data centers Energy conservation Genetic algorithms |
| dc.title.none.fl_str_mv | Optimizing Energy Consumption of Cloud Computing IaaS |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/doctoralThesis |
| description | A Master of Science thesis in Computer Engineering by Huda Ibrahim Mohamed entitled, "Optimizing Energy Consumption of Cloud Computing IaaS," submitted in May 2017. Thesis advisor is Dr. Raafat Aburukba and thesis co-advisor is Dr. Khaled El-Fakih. Soft and hard copy available. |
| format | doctoralThesis |
| id | aus_f5e60ea6a06eb9526e931e148dfd39f1 |
| identifier_str_mv | 35.232-2017.23 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/8909 |
| publishDate | 2017 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Optimizing Energy Consumption of Cloud Computing IaaSMohamed, Huda IbrahimCloud computingtask schedulingoptimizationinteger linear programmingpower consumptiongenetic algorithmsCloud computingData centersEnergy conservationGenetic algorithmsA Master of Science thesis in Computer Engineering by Huda Ibrahim Mohamed entitled, "Optimizing Energy Consumption of Cloud Computing IaaS," submitted in May 2017. Thesis advisor is Dr. Raafat Aburukba and thesis co-advisor is Dr. Khaled El-Fakih. Soft and hard copy available.Cloud computing infrastructures are designed to support the accessibility and availability of various services to consumers over the Internet. Datacenters hosting Cloud applications consume massive amounts of power, contributing to high carbon footprints to the environment. Hence, Green Cloud computing solutions are needed within the Cloud datacenters that optimize the energy consumption. The main objective of this thesis is to address the problem of power and carbon efficient resource management in a Cloud datacenter. This work focuses on the development of a dynamic task scheduling algorithm to enhance the datacenter power efficiency over time. To achieve this objective, a formal optimization model is proposed using Integer Linear Programming (ILP) that minimizes the energy consumption in a Cloud datacenter. The model is verified using exact techniques and the Genetics Algorithm (GA) heuristic-based technique. Furthermore, an adaptive GA is proposed to reflect the dynamic nature of the Cloud computing environment. The proposed adaptive GA is validated by simulating an IaaS Cloud environment and conducting a set of performance and quality evaluation study in this environment. The results demonstrate that the proposed solution offers performance gains with regards to response time and in reducing the power consumption in the Cloud datacenter.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE)Aburukba, RaafatEl Fakih, Khaled2017-09-11T08:32:12Z2017-09-11T08:32:12Z2017-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2017.23http://hdl.handle.net/11073/8909en_USoai:repository.aus.edu:11073/89092025-06-26T12:09:50Z |
| spellingShingle | Optimizing Energy Consumption of Cloud Computing IaaS Mohamed, Huda Ibrahim Cloud computing task scheduling optimization integer linear programming power consumption genetic algorithms Cloud computing Data centers Energy conservation Genetic algorithms |
| status_str | publishedVersion |
| title | Optimizing Energy Consumption of Cloud Computing IaaS |
| title_full | Optimizing Energy Consumption of Cloud Computing IaaS |
| title_fullStr | Optimizing Energy Consumption of Cloud Computing IaaS |
| title_full_unstemmed | Optimizing Energy Consumption of Cloud Computing IaaS |
| title_short | Optimizing Energy Consumption of Cloud Computing IaaS |
| title_sort | Optimizing Energy Consumption of Cloud Computing IaaS |
| topic | Cloud computing task scheduling optimization integer linear programming power consumption genetic algorithms Cloud computing Data centers Energy conservation Genetic algorithms |
| url | http://hdl.handle.net/11073/8909 |