A Learning Automata Based Dynamic Resource Provisioning in Cloud Computing Environments
Hamid Reza Qavami, Shahram Jamali, Mohammad Kazem Akbari, Bahman Javadi · 2017
Cloud computing provides more reliable and flexible access to IT resources, on-demand and self-service service request are some key advantages of it. Managing up-layer cloud services efficiently, while promising those advantages and SLA, motivates the challenge of provisioning and allocating resource on-demand in infrastructure layer, in response to dynamic workloads. Studies mostly have been focused on managing these demands in the physical layer and few in the application layer. This paper focuses on resource allocation method in application level that allocates an appropriate number of virtual machines to an application which requires a dynamic amount of resources. A Learning Automata based approach has been chosen to implement the method. Experimental results demonstrate that the proposed technique offers more cost effective resource provisioning approach while provisions enough resource for applications.