ong with SDN and Software Defined Compute (SDC) (where in computing is virtualized and software defined), creates Software Defined Infrastructure (SDI). SDI is the set of 3 components SDN, SDS and SDC making a new kind of software defined IT infrastructure where centralization and virtualization are the main focus. SDI is proposed to have infrastructure developed over commodity hardware and software stack defined over it SDS is exploiting the same concept of decoupling and centralization in reference to storage solutions as in SDN. The SDN works on decoupling the control plane with the data plane from a layer 3 switches and make a centralized decision point called the controller. The SDS works in the similar way by moving the decision making from the storage hardware to a centralized server. It helps in developing new and existing storage solutions over the commodity storage devices. The centralization helps to create a better dynamic solution for satisfying the user need. It also provides cheaper solution due to use of commodity hardware. The fourteenth chapter discusses about learning of SDN with software defined area. In this chapter, author tried to introduce a new approach which is based on the complex network processing and forecasting for an event. As we know the Internet is one of the finest examples of complex networks, we consider a networking device as a processing node where information comes in the form of packets and processed by the device. This functionality can be organized with a combination of machine learning algorithm and static nature of unprocessed network. Because of periodic request and response based services one network can be easily automated and controlled by a single administrator. Such type of functionalities can be made better if we can design our network having more iterative nature. Iterative nature means where request and responses are similar in nature. A network is very vulnerable to attack SO considering time series analysis of past finite time duration dataset, our network c