Machine Learning Approaches for Resource Allocation in the Cloud: Critical Reflections

Resource Allocation is the effective and efficient use of a Cloud's resources and is a very challenging problem in cloud environments. Many attempts have been made to make Resource Allocation automated and optimal in terms of profit. The best of these methods used Machine Learning, but this comes with an overhead for computation. A lot of research has been done in this domain to find more efficient methods. Distributed Neural Networks (DNN) is the future of computation and will soon be used to make the computation of large-scale data faster and easier. DNN is currently the most researched area. This paper will summarize the major research works in these fields. A new taxonomy is proposed and can be used as a reference for all future research in this domain. The paper also proposes some areas that need more research in the foreseeable future.