A Survey on Auto Scaling of Internet Application in a Cloud Environment?

Automatic scaling and dynamic resource management in cloud server provisioning has become an active area of research in the Cloud Computing paradigm. Cost of resources varies significantly depending on configuration for using them. Hence efficient management of resources is of prime interest to both Cloud Providers and Cloud Users. In this work we suggest a probabilistic resource provisioning approach that can be exploited as the input of a dynamic resource management scheme. Using resource on Demand use case to justify our claims, we propose a class constraint bin packing technique with online colour set algorithm inspired from standard models developed to represent sudden and intense workload variations. We show that the resulting model verifies Deterministic algorithms that statistically characterize extreme rare events, such as the ones produced by varying resource demands that may cause workload overflow in the resource on demand context. This analysis provides valuable insight on expectable abnormal behaviors of systems. We exploit the information obtained using Deterministic algorithms for the proposed on Demand use-case for defining policies (Service Level Agreements). We believe these policies for elastic resource provisioning and usage may be of some interest to all stakeholders in the emerging context of cloud networking.