Socio Fuzzy Based Performance Evaluation of Cloud Computing Service Model (IaaS)

Socio fuzzy based research is primarily focused on recovery of disaster in cloud computing and the spread of this technology with an enormous speed, which is sufficient to explain the need and desirability of this technology, on the other hand, same distinction is also the main challenge i.e. unplanned growth of cloud computing and relevant technologies. In past we have seen the same issues with World Wide Web, in which we have expanded to such levels that a proper governance and maintenance becarne near to impossible. Rapidly expanding cloud technology with conventional and emerging services is a source of generating huge volumes of data that requires to be addressed for analytics and simply for suitable storage structure. Big data and Intenet of things (IoT) are two emerging challenges linked to cloud computing and these two areas are research focus of many scientists. In this research we have proposed a Fuzzy inference system (FIS) which is a blend of cloud technology along with artificial intelligence and cognitive science. We believe that an autonomous and self-evolving intelligent environn•ment is the solution to emerging problems related to cloud technologies. To address the issues of big data and IOT, our proposed model FIS is having the ability to analyze the heterogeneity and homogeneity knowledge structures wherein, machine learning and artificial neural networks have been proposed for semantic, property and feature analysis- Validation of the proposed model FIS is being done through algorithm development as well as by simulating the model in B/IATLAB. Results have shown the positive inclination towards ecosystem relevance with overall perforrnance and interoperability i.e. These two characteristics play a vital role in the intelligent recovery system's long-term viability, while third pararneter is dynamic which may change as per the requirement e.g. reliability, security, cost etc. This research concludes that cloud technology will work better in a comprehensive cloud ecosystem with better management and service parameters for users for cloud-service providers, also the issues of big data and IoT are more manageable and observable in a cloud ecosystem.