Search

Scalability, performance, optimization and security requirements of 5G are easily managed by the software-defined platforms and virtualization. Anytime, anywhere user access with QoS and business process automation demands agile and flexible 5G architecture. In time and space domain, the traffic demands are variable in nature. Heterogeneous traffic generated by massive IoT devices and machine-to-machine communication can easily handle with flexible and reconfigurable network in a cost-effective manner. Dynamic resource scheduling and on-the-fly MAC reconfiguration heuristic can improve the performance of heterogeneous network access and minimize latency. Content and context-aware reconfigurable radio platforms with sensors can easily predict interference source and modify protocol according to requirements. Knowledge of traffic and content can reduce the congestion in the network and enhance the performance and efficient utilization of the resources. In this paper, we analyze SDN controller with NFV, and CRAN is the key enabler for 5G architecture.

Zero Touch network requires no human involvement other than high level implementation and declarative independent intents. Machine and human interaction learning help machines to achieve the human objective efficiently and enhances the security domain. At the different places of the network, computation and intelligence decisions with cloud environment will enhance the performance of the network. Scalability and heterogeneity in IoT framework are important parameters for performance of 6LoWPAN network. Protocol stack of NGN is a key part of protocol for supporting limited processing capabilities, low memory and limited power constrained power supply devices to Internet. Heavy network traffic causes congestion in the network which degrades the network performance and influences the QoS aspects goodput, throughput, E2E delay, jitter, Energy consumption, reliability and latency. Numerous congestion control heuristics are discussed based on traffic modeling, queue management and hybrid algorithms. This paper represents the queue management in the heterogeneous ad hoc network. Impact of minimum and maximum value of queue size on goodput and with respect of packet size is discussed in this paper. Throughput, delay and Jitter for different objective functions are compared and burst rate in case of 6LoWPAN is represented. For IoT application requirements, a novel traffic modeling based on congestion for future work is summarized.