Modeling of Systems Under Cloud Environment

Abstract

The emergence of large amount of data requires an efficient means of processing and storage facilities. Cloud computing provides an effective solution; MapReduce programming paradigm has the ability to handle such data by implementing Hadoop, but came up with some conflicting challenges in terms of Service Level Agreement (SLA) between major stakeholders. This paper focuses on coming up with a MapReduce model through system identification in order to address the requirement of the service time to meet-up the SLA within the limit of defined threshold in the presence of uncertainties in the system. A second order nonlinear model was obtained, which shows a good representation of the real system and could be used to develop control laws on the real system.