A Cost-AWARE Approach Based ON Learning Automata FOR Resource Auto-Scaling IN Cloud Computing Environment
Khosro Mogoui, Mostafa Ghobaei‐Arani · International Journal of Hybrid Information Technology · 2015
In recent years, applications of cloud services have been increasingly expanded. Cloud services, are distributed infrastructures which develop the communication and services. Auto scaling is one of the most important features of cloud services which dedicates and retakes the allocated dynamic resource in proportion to the volume of requests. The Scaling tries to utilize maximum power of the available resources also to use idle resources, in order to maximize the efficiency or shutdown unnecessary resources to reduce the cost of running requests. In this paper, we have suggested an approach based on learning automata for resource auto-scaling, in order to manage and optimize factor cost. Results of simulation show that proposed approach has been able to optimize cost compared to the other approaches.