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Proposed algorithm for optimal resource allocation for cloud computing environments / Naglaa Sayed Abdelrehem Mohamed ; Supervised Imane Aly Saroit Ismail , Fathi Ahmed Amer , Mohamed Fakhri Mahrous

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Naglaa Sayed Abdelrehem Mohamed , 2020Description: 123 Leaves : charts , facimiles ; 30cmOther title:
  • خوارزم مقترح للتوزيع الأمثل للموارد لبيئات الحوسبة السحابية [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Computers and Artificial Intelligence - Department of Information Technology Summary: Cloud Computing is defined using common software, infrastructure, virtual machines (VMs), and other cloud resources as services. It is a computing model in which customers can get their required infrastructure without the need to buy it. As the concept of hiring, customers pay only for what they use and can be used on request.The scheduling process on cloud computing is a method used to define the most convenient deployment for the available tasks, resources, or jobs on the cloud. In other words, cloud scheduling is to find the appropriate function that maps tasks into their best matching virtual machines.There are many various cloud scheduling algorithms used to coordinate between the tasks and the appropriate resources to get the best and most efficient way of resources usage, considering some measurement factors to get the least value of time, minimum value of cost, minimum value of delay and to maximize the resources utilization. This thesis presents a newly proposed model called Dynamic Three Stages Task Scheduling Algorithm (DTSTSA) and assesses it based on different performance metrics.The DTSTSA works as a strategy of three stages. In the first stage, a job classifier is used for task classification; it helps to pre-create different types of virtual machines based on a last documented historical database, to predict the most common task types and their appropriate matching virtual machine types. It saves the time needed to create virtual machines during the scheduling process
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.01.M.Sc.2020.Na.P (Browse shelf(Opens below)) Not for loan 01010110082774000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.01.M.Sc.2020.Na.P (Browse shelf(Opens below)) 82774.CD Not for loan 01020110082774000

Thesis (M.Sc.) - Cairo University - Faculty of Computers and Artificial Intelligence - Department of Information Technology

Cloud Computing is defined using common software, infrastructure, virtual machines (VMs), and other cloud resources as services. It is a computing model in which customers can get their required infrastructure without the need to buy it. As the concept of hiring, customers pay only for what they use and can be used on request.The scheduling process on cloud computing is a method used to define the most convenient deployment for the available tasks, resources, or jobs on the cloud. In other words, cloud scheduling is to find the appropriate function that maps tasks into their best matching virtual machines.There are many various cloud scheduling algorithms used to coordinate between the tasks and the appropriate resources to get the best and most efficient way of resources usage, considering some measurement factors to get the least value of time, minimum value of cost, minimum value of delay and to maximize the resources utilization. This thesis presents a newly proposed model called Dynamic Three Stages Task Scheduling Algorithm (DTSTSA) and assesses it based on different performance metrics.The DTSTSA works as a strategy of three stages. In the first stage, a job classifier is used for task classification; it helps to pre-create different types of virtual machines based on a last documented historical database, to predict the most common task types and their appropriate matching virtual machine types. It saves the time needed to create virtual machines during the scheduling process

Issued also as CD

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