Elastic cloud computing aided by history-based computacionaise agents to web service

Author(s)

Ariel da Silva Dias

• Document type: Master's Dissertation
• Press: São Carlos.
• Institution: Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB)
• Defense date: 2014-12-15

Examining board members

Marcos José Santana; Júlio Cezar Estrella; Celso Massaki Hirata

• Advisor: Marcos José Santana

Abstract

The efficient management of computational resources in the cloud is directly linked to correctly manage the performance of the applications hosted in the virtual machine (Virtual Machine - VM), creating an environment able to control it and resize features Memory, Disk, CPU and others resources, individually in response to workload. This work is also considered effective management which is possible to realize the return on investment for hiring the IaaS service. This Master thesis, is proposed the management of computing infrastructure in the cloud, using two models that facilitate self-adaptive resource provisioning in a virtualized environment using resource allocation model to predict the future workload and adaptive self-management capacity utilizing computational agents to continuously monitor the VMs. Furthermore, it is proposed return on investment, which is the ratio between the value that the client hired the IaaS service and how effectively it is using. Thus, each period is accounted for the rate of the amount spent in monetary units. To address this proposal, were developed algorithms that are the core of all management. Experiments were also conducted and the results show the ability of self-management for virtual machines with dynamic reconfiguration of infrastructure through predictions based on historical and also the reconfiguration and monitoring with the use of computational agents. After the analysis and evaluation of the results obtained in the experiments, is possible say that there was a significant improvement in reconfiguration of resources with computational agents compared with the workload forecast. (AU)

• FAPESP's process: 12/10777-0 - Elastic Cloud Computing aided by computational agents and based on history for Web Services.
• Grantee: Ariel da Silva Dias
• Support Opportunities: Scholarships in Brazil - Master