Title :
Prediction-Based Instant Resource Provisioning for Cloud Applications
Author :
Khatua, Sunirmal ; Manna, Moumita Mitra ; Mukherjee, Nandini
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Calcutta, Kolkata, India
Abstract :
Dynamic provisioning of computing resources to fulfill the application requirement based on its current demand is one of the key challenges in cloud environment. However, availability of a resource to the application is not possible just by launching the VMs, but by the subsequent reconfiguration of the provisioned VMs, which is time-consuming and application dependent. In order to solve the instant resource provisioning problem, in this paper we propose to use some auto-scaling techniques based on prediction and proportional thresholding.
Keywords :
cloud computing; resource allocation; virtual machines; application requirement; auto-scaling techniques; cloud applications; cloud environment; dynamic computing resource provisioning; prediction thresholding; prediction-based instant resource provisioning; proportional thresholding; provisioned VM; resource provisioning problem; Educational institutions; Forecasting; Load modeling; Monitoring; Prediction algorithms; Resource management; Time series analysis; Auto Scaling; Cloud Computing; Instant Resource Provisioning; Proportional Thresholding;
Conference_Titel :
Utility and Cloud Computing (UCC), 2014 IEEE/ACM 7th International Conference on
Conference_Location :
London
DOI :
10.1109/UCC.2014.92
