Implementation and Evaluation of Activity-Based Congestion Management Using P4 (P4-ABC)

Activity-Based Congestion management (ABC) is a novel domain-based QoS mechanism providing more fairness among customers on bottleneck links. It avoids per-flow or per-customer states in the core network and is suitable for application in future 5G networks. However, ABC cannot be configured on standard devices. P4 is a novel programmable data plane specification which allows defining new headers and forwarding behavior. In this work, we implement an ABC prototype using P4 and point out challenges experienced during implementation. Experimental validation of ABC using the P4-based prototype reveals the desired fairness results

Accelerating Network Functions using Reconfigurable Hardware. Design and Validation of High Throughput and Low Latency Network Functions at the Access Edge

Providing Internet access to billions of people worldwide is one of the main technical challenges in the current decade. The Internet access edge connects each residential and mobile subscriber to this network and ensures a certain Quality of Service (QoS). However, the implementation of access edge functionality challenges Internet service providers: First, a good QoS must be provided to the subscribers, for example, high throughput and low latency. Second, the quick rollout of new technologies and functionality demands flexible configuration and programming possibilities of the network components; for example, the support of novel, use-case-specific network protocols. The functionality scope of an Internet access edge requires the use of programming concepts, such as Network Functions Virtualization (NFV). The drawback of NFV-based network functions is a significantly lowered resource efficiency due to the execution as software, commonly resulting in a lowered QoS compared to rigid hardware solutions. The usage of programmable hardware accelerators, named NFV offloading, helps to improve the QoS and flexibility of network function implementations. In this thesis, we design network functions on programmable hardware to improve the QoS and flexibility. First, we introduce the host bypassing concept for improved integration of hardware accelerators in computer systems, for example, in 5G radio access networks. This novel concept bypasses the system’s main memory and enables direct connectivity between the accelerator and network interface card. Our evaluations show an improved throughput and significantly lowered latency jitter for the presented approach. Second, we analyze different programmable hardware technologies for hardware-accelerated Internet subscriber handling, including three P4-programmable platforms and FPGAs. Our results demonstrate that all approaches have excellent performance and are suitable for Internet access creation. We present a fully-fledged User Plane Function (UPF) designed upon these concepts and test it in an end-to-end 5G standalone network as part of this contribution. Third, we analyze and demonstrate the usability of Active Queue Management (AQM) algorithms on programmable hardware as an expansion to the access edge. We show the feasibility of the CoDel AQM algorithm and discuss the challenges and constraints to be considered when limited hardware is used. The results show significant improvements in the QoS when the AQM algorithm is deployed on hardware. Last, we focus on network function benchmarking, which is crucial for understanding the behavior of implementations and their optimization, e.g., Internet access creation. For this, we introduce the load generation and measurement framework P4STA, benefiting from flexible software-based load generation and hardware-assisted measuring. Utilizing programmable network switches, we achieve a nanosecond time accuracy while generating test loads up to the available Ethernet link speed

Consistent high performance and flexible congestion control architecture

The part of TCP software stack that controls how fast a data sender transfers packets is usually referred as congestion control, because it was originally introduced to avoid network congestion of multiple competing flows. During the recent 30 years of Internet evolution, traditional TCP congestion control architecture, though having a army of specially-engineered implementations and improvements over the original software, suffers increasingly more from surprisingly poor performance in today's complicated network conditions. We argue the traditional TCP congestion control family has little hope of achieving consistent high performance due to a fundamental architectural deficiency: hardwiring packet-level events to control responses. In this thesis, we propose Performance-oriented Congestion Control (PCC), a new congestion control architecture in which each sender continuously observes the connection between its rate control actions and empirically experienced performance, enabling it to use intelligent control algorithms to consistently adopt actions that result in high performance. We first build the above foundation of PCC architecture analytically prove the viability of this new congestion control architecture. Specifically, we show that, controversial to intuition, with certain form of utility function and a theoretically simplified rate control algorithm, selfishly competing senders converge to a fair and stable Nash Equilibrium. With this architectural and theoretical guideline, we then design and implement the first congestion control protocol in PCC family: PCC Allegro. PCC Allegro immediate demonstrates its architectural benefits with significant, often more than 10X, performance gain on a wide spectrum of challenging network conditions. With these very encouraging performance validation, we further advance PCC's architecture on both utilty function framework and the learning rate control algorithm. Taking a principled approach using online learning theory, we designed PCC Vivace with a new strictly socially concave utility function framework and a gradient-ascend based learning rate control algorithm. PCC Vivace significantly improves performance on fast-changing networks, yields better tradeoff in convergence speed and stability and better TCP friendliness comparing to PCC Allegro and other state-of-art new congestion control protocols. Moreover, PCC Vivace's expressive utility function framework can be tuned differently at different competing flows to produce predictable converged throughput ratios for each flow. This opens significant future potential for PCC Vivace in centrally control networking paradigm like Software Defined Networks (SDN). Finally, with all these research advances, we aim to push PCC architecture to production use with a a user-space tunneling proxy and successfully integration with Google's QUIC transport framework