Dynamic Shaping Method using SDN And NFV Paradigms

Traffic shaping controls communication traffic flow to prevent a specified communication rate from being exceeded. In conventional networks, the traffic shaping device is implemented at a predetermined location and only a communication flow passing through the device is targeted. If the traffic can be shaped dynamically on any selected communication flows at the optimal point only when necessary, it could use network bandwidths and packet relay processing capacity more efficiently and flexibly. This paper proposes a dynamic shaping method using Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) paradigms, which selects the optimal communication flows to be shaped, and the optimal shaping points dynamically. This paper also presented system configuration and functions for the proposed dynamic shaping, and the method to simplify the process of collecting the traffic data of each communication flow by SDN controller.

Support for 5G Mission-Critical Applications in Software-Defined IEEE 802.11 Networks

With the emergence of 5G networks and the stringent Quality of Service (QoS) requirements of Mission-Critical Applications (MCAs), co-existing networks are expected to deliver higher-speed connections, enhanced reliability, and lower latency. IEEE 802.11 networks, which co-exist with 5G, continue to be the access choice for indoor networks. However, traditional IEEE 802.11 networks lack sufficient reliability and they have non-deterministic latency. To dynamically control resources in IEEE 802.11 networks, in this paper we propose a delay-aware approach for Medium Access Control (MAC) management via airtime-based network slicing and traffic shaping, as well as user association while using Multi-Criteria Decision Analysis (MCDA). To fulfill the QoS requirements, we use Software-Defined Networking (SDN) for airtime-based network slicing and seamless handovers at the Software-Defined Radio Access Network (SD-RAN), while traffic shaping is done at the Stations (STAs). In addition to throughput, channel utilization, and signal strength, our approach monitors the queueing delay at the Access Points (APs) and uses it for centralized network management. We evaluate our approach in a testbed composed of APs controlled by SD-RAN and SDN controllers, with STAs under different workload combinations. Our results show that, in addition to load balancing flows across APs, our approach avoids the ping-pong effect while enhancing the QoS delivery at runtime. Under varying traffic demands, our approach maintains the queueing delay requirements of 5 ms for most of the experiment run, hence drawing closer to MCA requirements.