New novel idea for Cloud Computing: How can we use Kalman filter in security of Cloud Computing

Abstract

Cloud is a virtual image about some amount of undefined powers, that is widespread and had unknown power and inexact amount of hardware and software configurations, and because of we have not any information about clouds location and time dimensions and also the amounts of its sources we tell that Cloud Computing. This technology presents lots of abilities and opportunities such as processing power, storage and accessing it from everywhere, supporting, working - team group - with the latest versions of software and etc., by the means of internet. On the other hand, in such a large scale networks we should consider the reliability and powerfulness of such networks in facing with events such as high amount of users that may login to their profiles simultaneously, or for example if we have the ability to predict about what times that we would have the most crowd in network, or even users prefer to use which part of the Cloud Computing more than other parts - which software or hardware configuration. With knowing such information, we can avoid accidental crashing or hanging of the network that may be cause by logging of too much users. In this paper we propose Kalman Filter that can be used for estimating the amounts of users and software's that run on cloud computing or other similar platforms at a certain time. After introducing this filter, at the end of paper, we talk about some potentials of this filter in cloud computing platform. In this paper we demonstrate about how we can use Kalman filter in estimating and predicting of our target, by the means of several examples on Kalman filter.