Technological advancements have provided wireless links with very high data rate capacity for 5G/6G mobile networks and WiFi 6, which will be widely deployed by 2025. However, the capacity can have substantial fluctuations, violating the assumption at the transport layer that the capacity is (almost) steady. In this paper, we present a general and efficient, yet deployable solution to this problem through a novel design empowered with a rich theory, allowing a significantly improved experience in using new technologies, especially mobile cellular services. We employ the well-known theory of food-chain models in biology, where a bottleneck link can be modeled as prey, while flows are predators. We extend this model to a chain of predators and preys to form a multi-hop congestion controller, called LGCC. Through simulation evaluation with real-life 5G traces we show the effectiveness of LGCC, compared with the state-of-the-art ABC (Accel-Brake Control). Our results show an order of magnitude bottleneck queuing delay decrease, with only a small decrease in throughput because LGCC tries to never exceed link capacities. LGCC’s design can additionally open a new paradigm in stable multi-hop congestion control and flow aggregation.

Reliable consistent communication over millimeter-wave (mmWave) channels is a challenging problem due to their sensitivity to blocking of Line of Sight connections. MmWave is a key building block in 5G and future generation cellular networks, making solutions to this problem space important. Our aim is to use predictive control to manage and simultaneously use multiple available mmWave paths to achieve reliable consistent communication (i.e., steady transmission rate with low delay) with a multipath proxy. To this end we investigate transient solutions of Markov Modulated Fluid Queue models (MMFQ), apt because the mmWave blocking has been modeled with Markovian models. We propose a combination of models that can be solved using newly proposed matrix analytic techniques in a timely enough manner for use in real-time control. This gives us a prediction of either proxy queue distributions or probabilities of reaching proxy buffer levels over a short time horizon, enabling the proxy to make preemptive path decisions to maintain a desired Quality of Service. A proof of concept simulation study demonstrates the efficacy of our proposed MMFQ-based predictive approach over either static or purely reactive control approaches.

Most Internet hosts today support multiple access technologies and network interfaces. Multipath transport protocols, like MPTCP, are being deployed (e.g., in smartphones), allowing transparent simultaneous use of multiple links. Besides providing increased resilience to link failures, multipath transports may better exploit available (aggregate) capacity across all interfaces. The safest way to ensure fairness is to assume that any subflows of a multipath end-to-end connection may share bottleneck links, but knowledge of non-shared bottlenecks could allow multipath senders to exploit more capacity without being unfair to other flows. The problem of reliably detecting the existence of (non)-shared bottlenecks is not trivial and is compounded by the fact that bottlenecks may change due to traffic dynamics. In this paper we focus on practical methods to reliably group flows that share, possibly dynamic, bottlenecks online and in a passive manner (i.e., without injecting measurement traffic). We introduce a novel dynamic clustering algorithm that we apply to update our previous shared bottleneck flow grouping (SBFG) method standardized by the IETF, based on delay statistics. We also adapt an offline SBFG method based on wavelet filters to enable it for online operation. These SBFG methods are evaluated by a simple testbed, rigorous simulation and real-world Internet experiments in a testbed comprised of multihomed hosts. Our results suggest that there is no clear winner, and selection of the “best” SBFG method will have to consider tradeoffs regarding accuracy, lag, and application requirements.

Multipath TCP (MPTCP) enables the simultaneous use of multiple links for bandwidth aggregation, better resource utilization and improved reliability. Its coupled congestion control intends to reap the increased bandwidth of multiple links, while avoiding being more aggressive than regular TCP flows on every used link. We argue that this leads to a very conservative behavior when paths do not share a bottleneck. Therefore, in this paper, we first quantify the penalty of the coupled congestion control for links that do not share a bottleneck. Then, in order to overcome this penalty, we design and implement a practical shared bottleneck detection (SBD) algorithm for MPTCP, namely MPTCP-SBD. Through extensive emulations, we show that MPTCP-SBD outperforms all currently deployed MPTCP coupled congestion controls by accurately detecting bottlenecks. For the non-shared bottleneck scenario, we observe throughput gains of up to 40% with two subflows and the gains increase significantly as the number of subflows increase, reaching more than 100% for five subflows. Furthermore, for the shared bottleneck scenario, we show that MPTCP-SBD remains fair to TCP. We complement the emulation results with real-network experiments justifying its safeness for deployment.

Datacenter transport has attracted much recent interest, however, most proposed improvements require changing the datacenter fabric, which hinders their applicability and deployability over commodity hardware. In this paper, we present a novel congestion controller, Logistic Growth Control (LGC), for datacenters which does not require changes to the datacenter fabric. LGC uses a similar ECN marking as in DCTCP, but adapts to congestion using the logistic growth function. This function has been proven to have nice characteristics including stability, convergence, fairness, and scalability, which are very appealing for congestion control. As a result, our LGC mechanism operates in the datacenter network in a more stable and fair manner, leading to less queuing and latency. LGC also behaves better than DCTCP, and it converges to the fair share of the bottleneck link capacity irrespective of the Round-Trip-Time (RTT). We discuss the stability and fairness of LGC using a fluid model, and show its performance improvement with simulations.

When multiple congestion controlled flows traverse the same network path, their resulting rate is usually an outcome of their competition at the bottleneck. The WebRTC / RTCWeb suite of standards for inter-browser communication is required to allow prioritization. This is addressed by our previously presented mechanism for coupled congestion control, called the Flow State Exchange (FSE). Here, we present our first simulation results using two mechanisms that have been proposed for IETF standardization: Google Congestion Control (GCC) and Network-Assisted Dynamic Adaptation (NADA). These two mechanisms exhibit aspects that allow us to use a simpler “passive” algorithm in our FSE. Passive coupling allows a less time-constrained request-response style of signaling between congestion control mechanisms and the FSE, which enables the FSE to run as a stand-alone management tool.

Practical shared bottleneck detection has proved to be a difficult problem. We present a novel passive approach using efficient estimates of time and frequency domain summary statistics. The approach is not CPU nor network intensive, and has numerous potential applications in the Internet. Simulations and tests over the Internet and 3G cellular network show its efficacy in grouping flows correctly.

Consumer broadband services are increasingly a mix of TCP-based and UDP-based applications, often with quite distinct requirements for interactivity and network performance. Consumers can experience degraded service when application traffic collides at a congestion point between home LANs, service provider edge networks and fractional-Mbit/sec `broadband' links. We illustrate two key issues that arise from the impact of TCP-based data transfers on real-time traffic (such as VoIP or online games) sharing a broadband link. First, well-intentioned modifications to traditional TCP congestion control can noticeably increase the latencies experienced by VoIP or online games. Second, superficially-similar packet dropping rules in broadband gateways can induce distinctly different packet loss rates in VoIP and online game traffic. Our observations provide cautionary guidance to researchers who model such traffic mixes, and to vendors implementing equipment at either end of consumer links.

TCP is quite a heavyweight protocol when serving very small web pages. We introduce a server-side kernel modification which enables a web server to perform HTTP over a UDP socket while the kernel provides a regular TCP interface 'on the wire' to remote clients. We show that our 'stateless' TCP modification can greatly reduce a server's CPU usage (>20%) and TCP related memory requirements(>90%), potentially enabling it to serve small web pages even under extreme overload conditions.

Loss based TCP congestion control has been shown to not perform well in environments were there is non-congestion related packet losses. Delay based TCP congestion control algorithms provide a low latency connection with no congestion related packet losses, and have the potential for being tolerant to non-congestion related losses. Unfortunately, delay based TCP does not compete well with loss based TCP, currently limiting its deployment. We propose a delay based algorithm which extends work by Budzisz et al. to provide tolerance to non-congestion related losses, and better coexistence with loss based TCP in lightly multiplexed environments. We demonstrate that our algorithm improves the throughput when there are 1% packet losses by about 150%, and gives more than 50% improvement in the ability to share capacity with NewReno in lightly multiplexed environments.

Wireless local area networks have developed into a promising solution to support advanced data services in untethered environments. Selection of an efficient packet-scheduling scheme is important for managing the bandwidth while satisfying QoS requirements of active sessions having diverse traffic characteristics. The key difficulty is the distributed nature of the queues in the uplink, resulting in the scheduler having to trade off polling greedy stations against wasting resources by polling potentially idle stations. In order to address this, we propose a novel scheduling scheme, "embedded round robin", which dynamically classifies stations as "busy" and "clear". We then extend the previously proposed dual queue scheduling discipline to the case of wireless networks.

In this paper we focus on real-time scheduling of "soft" real-time data services such as multimedia data, MPEG video streaming and IP telephony, which can tolerate a small degree of loss or delay. We argue that network operators and service providers should be able to select from a range of quality of service objectives, including maximizing the number of customers receiving good service. Further, we argue that scheduling disciplines such as fair queueing are unable to achieve such goals and hence there is a need for alternative approaches. We propose a new scheduling scheme, which we call the dual queue discipline. We show that the dual queue has the flexibility to satisfy a variety of QoS objectives, ranging from existing notions of fairness through to maximizing the number of customers receiving good service. In addition, even the simplest dual queue implementation outperforms fair queueing, is scalable in the number of active sessions, and can be made fair, if desired, over moderate to long time scales.