An Approach for Dynamic Scaling of Resources in Enterprise Cloud

• Published in: 2013 IEEE 5th International Conference on Cloud Computing Technology and Science Vol. 2; pp. 345 - 348
• Main Authors: Kanagala, Kartheek, Sekaran, K. Chandra
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2013
• Subjects: Auto-scale; Cloud; Cloud computing; Conferences; DES; Forecasting; IaaS; Monitoring; SLA; Smoothing methods; Time factors; Virtual Machines
• DOI: 10.1109/CloudCom.2013.167

Elasticity is one of the key governing properties of cloud computing that has major effects on cost and performance directly. Most of the popular Infrastructure as a Service (IaaS) providers such as Amazon Web Services (AWS), Windows Azure, Rack space etc. work on threshold-based auto-scaling. In current IaaS environments there are various other factors like "Virtual Machine (VM)-turnaround time", "VM-stabilization time" etc. that affect the newly started VM from start time to request servicing time. If these factors are not considered while auto-scaling, then they will have direct effect on Service Level Agreement (SLA) implementations and users' response time. Therefore, these thresholds should be a function of load trend, which makes VM readily available when needed. Hence, we developed an approach where the thresholds adapt in advance and these thresholds are functions of all the above mentioned factors. Our experimental results show that our approach gives the better response time.