Today's fast-growing Video-on-Demand (VoD) service needs efficient content delivery to guarantee the user experience. To reduce costs, the industry has been exploring the adoption of unstable, heterogeneous, low-performance edge nodes as cost-efficient alternatives to expensive CDN servers. To compensate for the resulting degradation in user experience, Multi-source Parallel Downloading (MPD) is becoming a new VoD transport paradigm. However, existing transport optimization solutions face performance obstacles when applied to the MPD scenarios. They cannot handle the contention between MPD flows of the same download task, which is likely to occur at the shared last-hop, and lack the ability to quickly adapt to the unstable network environments brought by dynamic, heterogeneous, and low-performance edge nodes. To fill this gap, we propose Hermit, a VoD-oriented MPD transport algorithm. Hermit (1) continuously monitors the state of the flows and makes timely scheduling decisions, and (2) efficiently coordinates across the flows to mitigate self-contention at the shared last hop. As a client-driven scheme, Hermit does not require cumbersome coordination among edge nodes, nor does it increase server complexity. Through extensive experiments on real-world large-scale testbed and locally emulated network conditions, we demonstrate that Hermit can improve the consistent downloading rate by 9.2% to 21.3%.

QUIC gains significant attention due to its superior transmission performance, achieving widespread adoption in both academia and industry. To improve round-trip time (RTT) estimation, QUIC introduces the Host Delay field, enabling senders to exclude receiver-induced delays. Many delay-based congestion control algorithms (CCAs) rely on these RTT estimates to detect congestion and regulate sending rates. However, we find that malicious Host Delay values can distort RTT measurements, causing inappropriate rate adjustments by CCAs.In this paper, we investigate a new class of attacks leveraging maliciously crafted Host Delay values. To our knowledge, we are the first to analyze the vulnerability of Host Delay and present QUDIT, a universal receiver-driven attack targeting delay-based QUIC CCAs. Unlike prior attacks that presume full network queuing delays visibility and undetected injection capabilities, our attacker model only grants the adversary access as a standard QUIC receiver with limited knowledge of bottleneck conditions. We minimally modify the QUIC receiver to infer bottleneck queuing behavior in real time. Based on these inferences, we design dynamic Host Delay crafting strategies tailored to the specific behavior of various delay-based CCAs and accounting for random network fluctuations. Our attack prompts the sender to overshoot its rate, leading to excessive bandwidth consumption at the bottleneck and degradation of competing flows. Results demonstrate the throughput degradation of victim flow achieves up to 60% within 0.3 s and amplification gains between 200× and 600×. We propose defenses mitigating QUDIT, with vulnerabilities reported to IETF and QUIC maintainers.

Multi-site Parallel Downloading is a technique that uses multiple low-cost edge nodes in the Internet to transfer short video content. Traditional multi-path congestion control fails to achieve fast convergence and high bandwidth utilization in MPD scenarios due to the over-coupling of subflows. In this paper, we propose a semi-coupled congestion control design for the MPD scenario by reallocating traffic between independent subflows. In simulation experiments, our design outperforms baseline models of traditional MPTCP.

To improve the performance of mobile web services, a new transport protocol, QUIC, has been recently proposed as a substitute for TCP. However, with pros and cons of QUIC, it is challenging to decide whether and when to use QUIC in large-scale real-world mobile web services. Complex temporal correlation of network conditions, high user heterogeneity in a nationwide deployment, implementation diversity of QUIC variants limited, and resources on mobile devices all affect the selection of transport protocols. In this paper, we present WiseTrans, an adaptive transport protocol selection mechanism, to switch transport protocols for mobile web services online and improve the completion time of web requests. WiseTrans introduces machine learning techniques to deal with temporal heterogeneity, makes decisions with historical information to handle spatial heterogeneity, adopts an online learning method to keep pace with implementation variation, and switches transport protocols at the request level to reach high performance with acceptable overhead. We implement WiseTrans on two platforms (Android and iOS) in a popular mobile web service application of Baidu. Comprehensive experiments demonstrate that WiseTrans can reduce request completion time by up to 25.8% on average compared to the usage of a single protocol.