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

Abstract

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.

SD-RAN Interactive Management Using In-band Network Telemetry in IEEE 802.11 Networks

“…With the improvements in radio resource utilization provided by the IEEE 802.11n amendment [25], researchers focused on channel optimization and fairness (e.g., modifying or predicting the Aggregated MAC Service Data Unit (A-MSDU) behavior) [50,35,5,39,54]. To overcome the the well-known IEEE 802.11 Performance Anomaly [20] and enhance the QoS delivery, researchers have been addressing infrastructure sharing via network slicing [46,48,22,4,21,11,27,28,47,30]. Although most work has been only assessed via simulation, there were several practical implementations as well [22,4,21,11].…”

“…Thus, taking advantage of such frameworks, researchers have been proposing different sorts of user association algorithms and thus enhancing load balancing of flows across APs mobility support, fairness, and QoS [31] [30] [12,16,67]. Generally, such user association algorithms have been proposed aiming to minimize the average number of STAs assigned to an AP and maximize the overall throughput of the network and Received Signal Strength Indicator (RSSI) [30].…”

“…Yet, verifying the QoS E2E throughout a wireless network remains challenging. In our previous work [27] [28] [31] [30] we studied the impact of performing airtime-based network slicing and user association at the RAN. However, only a coarse-grained level of monitoring was addressed and, hence, limiting the understanding and the insights about the network behavior.…”

“…In our previous work [27,31,28,30] we pursued enhanced QoS delivery by performing airtime-based network slicing and user association at the IEEE 802.11 RAN while performing traffic shaping at the end devices. However, we addressed only a coarse-grained level of monitoring and, hence, limited the understanding and insights about the network behavior.…”

“…In previous work, we evaluated the impact of airtime-based network slicing on the E2E latency using the Internet Control Message Protocol (ICMP) [44] protocol and we exploited its potential to guarantee latency-related requirements [27]. Thereafter, besides developing and integrating queueing delay measurements of Access Points (APs) into the formulation of a QoS optimization problem [28], we proposed a delay-aware approach for performing runtime Medium Access Control (MAC) management via airtime-based network slicing, traffic shaping, and user association using Multi-Criteria Decision Analysis (MCDA) [31,30]. Although we identified that stringent QoS requirements of 5G Mission-Critical Applications (MCAs) can be potentially met and the pingpong effect can be avoided, our approach was limited to the coarse-grained level of the monitoring statistics collected at the APs.…”