QUIC is a new protocol standardized in 2021 designed to improve on the widely used TCP / TLS stack. The main goal is to speed up web traffic via HTTP, but it is also used in other areas like tunneling. Based on UDP, it offers features like reliable in-order delivery, flow and congestion control, stream-based multiplexing, and always-on encryption using TLS 1.3. Unlike TCP, QUIC integrates these capabilities in user space, relying on kernel interaction solely for UDP. Operating in user space allows more flexibility but sacrifices some kernel-level efficiency and optimization that TCP benefits from. Various QUIC implementations exist, each distinct in programming language, architecture, and design. QUIC is already widely deployed on the Internet and has been evaluated, focussing on low latency, interoperability, and standard compliance. However, benchmarks on high-speed network links are still scarce. This paper presents an extension to the QUIC Interop Runner, a framework for testing the interoperability of QUIC implementations. Our contribution enables reproducible QUIC benchmarks on dedicated hardware and high-speed links. We provide results on 10G links, including multiple implementations, evaluate how OS features like buffer sizes and NIC offloading impact QUIC performance, and show which data rates can be achieved with QUIC compared to TCP. Moreover, we analyze different CPUs and CPU architectures influence reproducible and comparable performance measurements. Furthermore, our framework can be applied to evaluate the effects of future improvements to the protocol or the OS. Our results show that QUIC performance varies widely between client and server implementations from around 50 Mbit/s to over 6000 Mbit/s. We show that the OS generally sets the default buffer size too small. Based on our findings, the buffer size should be increased by at least an order of magnitude. Our profiling analysis identifies Packet I/O as the most expensive task for QUIC implementations. Furthermore, QUIC benefits less from AES NI hardware acceleration while both features improve the goodput of TCP to around 8000 Mbit/s. The lack of support for NIC offloading from QUIC implementations results in missed opportunities for performance improvement. The assessment of CPUs from different vendors and generations revealed significant performance variations. We employed core pinning to examine if the performance of QUIC implementations is affected by the allocation to specific CPU cores. The results indicated an increased goodput of up to 20% when running on a specifically chosen core compared to a randomly assigned core. This outcome highlights the impact of CPU core selection on the performance of QUIC implementations but also for reproducible measurements.

Time-synchronous online examinations pose new demands on our infrastructure: lectures with more than 1000 students are common at TUM, and in case of time-synchronous examinations students concurrently download working instructions or submit solutions – with possibly multiple such examinations being conducted at the same time. Furthermore, the architecture has to withstand students that impatiently reload the download page multiple times as well as the sudden increase in traffic at the start and end of an exam. In addition, the architecture has to be resilient against both deliberate attacks of individuals and handling of unsuspecting users.In this paper we discuss our implementation of an examination management platform as multi-tenancy system based on operational requirements, demands on scalability, and bottlenecks we encountered in our attempt to roll out the infrastructure for as many examinations as needed.

Estimating the capacity of network paths is a frequently and versatilely used technique for network and flow analysis used by service providers and researchers to analyze available bandwidth, performance limitations of connections, or infrastructure deployments. While researchers evaluated different capacity estimation approaches in the early 2000s, there are no recent studies on the accuracy of estimates and capacity deployments in today’s Internet.This paper is purposed to survey the accuracy of actively conducted capacity estimation in today’s Internet. We implement passive packet pair dispersion-based capacity estimation according to the PPrate algorithm and conduct active measurements with TCP and ICMP traffic on controlled targets in the Internet and on public web servers to analyze the accuracy and stability of estimated capacities in the Internet.Our study confirms the general accuracy of PPD-based measurements through the Internet while we observe and discuss impacts by interrupt coalescence, receive offloading, and ICMP rate limiting of middleboxes. Measurements to over 3500 web servers taken from the Alexa top 1M list indicate capacities of at least 1 Gbit/s for the majority of paths to measurement targets, while ICMP-based measurements frequently result in significant underestimation due to ICMP rate limiting.

Byzantine fault tolerant (BFT) consensus allows the construction of robust, distributed systems via the state-machine replication (SMR) approach. Still, after more than 40 years of research, limitations on performance and scalability for practical systems remain. A large corpus of existing work improves on consensus complexity, performance and introduces a multitude of optimization techniques. The state-of-the-art is complex. On the other hand, many protocols designed for practical deployments are built on strong, common assumptions about underlying communication and authentication primitives. To fulfill these assumptions, often, commodity tools and libraries are employed without further analysis and caution for negative interplay.Instead of contributing to the existing complexity, we choose a different approach. In this paper, we outline the feasibility and potential impact of the optimization of common building blocks of BFT-SMR systems. We systemize existing work in terms of common model assumptions and identify optimization potential. Finally, we choose the building block of networking transport as a representative example and analyze its optimization space, both in context of general BFT-SMR systems and a case study of the HotStuff protocol. We describe behavior, challenges, and desired configuration of network transports for use in byzantine agreement, and identify lossy links as the main catalyst for significant performance differences between protocols and configurations.

Analyzing throughput limitations of TCP connections has been a frequently studied topic. While existing approaches determine throughput limitations for whole connections or specific segments of connections, this paper surveys whether such approaches can also be used to classify individual changes in the throughput of a connection.In this paper, we introduce an approach to classify changes in TCP throughput based on their coincide with changes between TCP transfer periods. We evaluate different change point detection methods with generated TCP traffic providing ground truth data regarding throughput changes. Further, we survey the matching between throughput change points and transfer periods in passively captured Internet traffic. We conclude that the classification of TCP throughput changes with TCP transfer periods is feasible for a significant share of changes and observe significant differences in matching results depending on the used change point detection method.

Languages for programming data planes like P4 sparked a plethora of new applications in the data plane. The dynamic, evolving environment makes it challenging to understand what performance can be expected when running a program in a specific data plane target. However, knowing this is crucial for network operators when upgrading their networks.

After nearly five years and 34 draft versions, standardization of the new connection oriented transport protocol QUIC was finalized in May 2021. Designed as a fundamental network protocol with increased complexity due to the combination of functionality from multiple network stack layers, it has the potential to drastically influence the Internet ecosystem. Nevertheless, even in its early stages, the protocol attracted a variety of parties including large providers. Our study shows, that more than 2.3 M IPv4 and 300k IPv6 addresses support QUIC hosting more than 30 M domains.

Monitoring and optimizing network performance is essential for data center operators and service providers. To better understand network performance, the throughput limiting factor of TCP connections can be analyzed. Previous research introduces approaches for the offline analysis of root causes of TCP throughput based on previously captured traffic. With increasing computational power and packet processing capabilities on commodity hardware, previously existing analysis limitations get overcome nowadays.This paper presents a scalable tool to analyze the throughput limitation of TCP flows in real-time, i.e., while the tool observes traffic on a network interface. We describe the adaption of existing approaches for TCP throughput limitation analysis and required passive capacity estimation to satisfy online analysis requirements.We evaluate the effectiveness and accuracy of our implementation with a generated data set for different TCP congestion control algorithms and varying network parameters. Furthermore, we survey the performance of our implementation with thousands of concurrent flows and discuss trade-offs and limitations of such sophisticated analysis in real-time.We provide our code as free and open-source.