Adaptive Neural Fuzzy Interface System for Cloud Computing (original) (raw)
Cloud computing is an improving area in research and in industry, which consists of distributed computing, internet, web services and virtualization.One of the most important technologies to load forecasting in the cloud computing is to ensure the maximize utilization of the system resource. Under the premise that the load is known in the next level, the cloud computing node can assign the physical machines in advance, and hence reduces the waiting time of the task, which also reduces the cloud computing node's resource consumption. A neural fuzzy technique called Adaptive network based fuzzy inference system (ANFIS) has been used as a prime tool in the present work. Using this hybrid method, at first an initial fuzzy model along with its input variables are derived with the help of the rules extracted from the input output data of the system that is being represented. Next the neural network is used to fine tune the rules of the initial fuzzy model to produce the final ANFIS model of the system. In this proposed work ANFIS is used as the backbone for the load balancing in the cloud computing. I. INTRODUCTION Adaptive network based fuzzy inference system (ANFIS) is a neuro fuzzy technique where the fusion is made between the neural network and the fuzzy inference system. In ANFIS the parameters can be estimated in such a way that both the Sugeno and Tsukamoto fuzzy models are represented by the ANFIS architecture. Again with minor constraints the ANFIS model resembles the Radial basis function network (RBFN) functionally. This ANFIS methodology comprises of a hybrid system of fuzzy logic and neural network technique. The fuzzy logic takes into account the imprecision and uncertainty of the system that is being modeled while the neural network gives it a sense of adaptability. Cloud computing is a new pattern of large-scale distributed computing. It has stimulated computing and data away from desktop and manageable PCs, into large data centers [1]. It has the ability to connect the power of Internet and wide area network (WAN) to make use of resources that are available remotely, thereby providing cost-effective solution to most of the real life requirements [2]. It gives the scalable IT resources such as applications and services, in addition to the infrastructure on which they control, over the Internet, on pay-per-use basis to regulate the capacity rapidly and easily. It helps to occupy changes in demand and helps any organization in stay away from the capital costs of software and hardware [3] [4]. Therefore, cloud computing is a structure for enabling an appropriate, on-demand network access to a common pool of computing resources.Cloud service is divided into three models. They are,as shown in Fig. 1. Cloud Software as a service (Saas): The competence provided to the consumer is to make use of the provider's applications consecutively running on a cloud communications. The applications are easy to get from several client devices throughout a thin client interface such as a web browser. The consumer does not deal with the fundamental cloud infrastructure. Cloud Platform as a Service (Paas): The capability provided to the consumer is to arrange on the cloud communications consumer formed or obtained applications created by means of programming languages and tools sustained by the provider. The consumer does not supervise or control the fundamental cloud structure, but has control over the applications and perhaps application hosting environment configurations.
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