Evolution of Artificial Intelligent Plane

Networks are evolving to meet user demands. Main qualities which make conventional internet successful are heterogeneity and generality combining with user transparency and rich functionality for end-to-end systems. In today's world networks display characteristics of unstable convoluted systems. Till date most networks are murky to its applications and providing only best effort delivery of packets with little or zero information about the reliability and performance characteristics of different paths. Granting, this design works well for simple server-client model, many emerging technologies such as: NFV (Network Function Virtualization [8], IoT (Internet of Things) [9], Software Defined Networking [10], CDN (Content Delivery Networks) [11] and LTE (Long-Term Evolution) [12] and 5G Cellular Networks [13] heavily depend on affluent information about the state of the network. For example, author in [14] described, if VNFs (Virtual Network Functions) [15] are not aware of the traffic on virtio interfaces assisting hypervisor, then this might result in a bottleneck in NFV infrastructure. In other words, VNFs should know the state of the network (in terms of traffic) to accelerate applications hosted across VNFs in NFV infrastrucutre. Authors in [16] explained the need of the data storage as the number of connected IoT devices are increasing on unprecedented level [17]. In order to optimize the data storage, it is imperative for IoT nodes to know about the other nodes and their transportation method of moving data among networks.