Dynamic quality of service concepts for wired and wireless networks

Abstract

The unprecedented increase of networked devices through the Internet of Things paved the way for Networked Control Systems (NCS), which are found all around us today. NCSs control physical processes over computer networks, for instance, in smart homes, smart factories, automobiles, or drone operations. While it is cost-efficient and flexible to use computer networks, the often stringent latency requirements of NCS make Quality of Service (QoS) models for the network communication essential. QoS models provision network resources and can be used to ensure latency and jitter guarantees for time-sensitive real-time traffic, or to improve reliability and fairness for best-effort network traffic. In order to provide latency guarantees, current QoS models require a strict traffic specification from the application. They then distinguish between two classes of network traffic: compliant traffic, which conforms to the traffic specification and receives the latency guarantees, and non-compliant traffic, which receives no guarantees at all. However, it is difficult to accurately predict and specify the network traffic of applications, especially for NCS that interact with the physical world. Moreover, the static nature of traditional QoS models, which only distinguish between compliant and non-compliant traffic, makes it dangerous to underestimate an application's traffic specification, as non-compliant traffic will lose its QoS guarantees, which could have catastrophic consequences for the safety of the system. Therefore, there is currently a gap for dynamic QoS models, that can react to and mitigate unexpected network conditions. In particular, they should be able to compensate for short-term traffic that is not conforming to the traffic specification (out-of-spec traffic) without losing all QoS guarantees. Furthermore, dynamic QoS models that can adapt to fluctuating network conditions are required for NCS with wireless networks, such as drone operations. In this thesis, we address the problem of unexpected network conditions that can occur when working with NCS. To this end, we investigate dynamic QoS models for both wired, time-sensitive networks and wireless, best-effort networks. In particular, we first address the problem of compensating for short-term non-compliant traffic in wired, time-sensitive networks, such as that of NCS. We propose the Dynamic Deterministic QoS model, which gracefully degrades QoS guarantees in case of short-term violations. It is implemented by the Dynamic Priority Token Bucket (DPTB), which is a proposed token bucket extension designed to work on top of existing scheduling algorithms, such as the IEEE Asynchronous Traffic Shaper. DPTB does not require any modifications to devices inside the network, only at the edge, and can provide weaker, yet still deterministic latency guarantees for excess packets. These provided sub-guarantees improve control performance and resource utilization efficiency of NCSs, which we demonstrate using a proposed physical NCS benchmark setup. Second, we address out-of-spec traffic in the form of delayed frames in time-based networks. We propose a frame elevation policy for the time-slotted IEEE Time-Aware Shaper (TAS) to enhance it with weakly-hard real-time capabilities. %The TAS is a popular QoS mechanism for providing real-time latency guarantees over Ethernet. By selectively elevating the priority of some delayed frames instead of dropping them, they are forwarded with highest priority to catch up with their original timeslot and meet their deadline. Implemented by a post-processing routine for existing TAS schedules, we propose modifications such that the original deadlines still hold even when elevated frames interrupt scheduled transmissions. We show that our elevation policy can be used to provide weakly-hard real-time guarantees for NCSs, with combined wireless and wired networks, using our physical benchmark setup. Third, we address the problem of fluctuating network conditions, caused by obstacles or frequency jamming attacks in wireless networks used for drone communication. A drone operation is an NCS, where the drone receives control commands from the ground control station (GCS) and replies with status updates over a wireless network. However, wireless communication differs from wired communication in that it is often error-prone and subject to interference or even jamming attacks. Therefore, we develop an adaptive drone communication redundancy (ADCR) mechanism that detects communication outages and mitigates them by dynamically adapting communication over heterogeneous, redundant network interfaces. We show that ADCR balances the trade-off between reliability and efficiency and provides similar reliability as fixed redundancy but at a significantly lower overhead. Fourth, we address fluctuating network conditions in the form of excessive latency in large-scale, public WiFi networks. Such public WiFi networks, for example, found in airports or public transportation today, often provide unsatisfactory QoS, caused by congestion delays. To this end, we propose a usage-dependent QoS model (UD-QoS) that dynamically classifies the network behavior of wireless devices and prioritizes those that cause lower network loads in case of congestion. We show that this shields interactive devices with low network usage from high latency, caused by congestion of packets from devices with high network usage. In addition, this dynamic QoS model provides an incentive for users to self-regulate, in order to receive better QoS in congested networks.