The Access Traffic Steering, Switching, and Splitting (ATSSS) technology, currently under standardization by the 3rd Generation Partnership Project (3GPP), is designed to enhance wireless access through the bundling of both 3GPP and non-3GPP access. One implementation option involves tunneling data through the Multipath QUIC (MP-QUIC) protocol. The decision of which access network each packet is transmitted on can greatly impact the performance of a network flow, and may also impact the performance of other flows. While Active Queue Management (AQM) in the network could normally manage such interactions, such techniques are limited in a shared multipath-tunnel context, since all traffic in the tunnel share a single connection. This paper introduces a multi-flow, multipath tunneling framework using MP-QUIC. It employs four distinct scheduling policies for packet scheduling decisions. We investigate how such scheduling policies interact with each other, and how they may be combined in order to achieve trade-offs in terms of latency, interactivity, and throughput. Through an extensive investigation in both emulated and real-world environments, we show that Quality of Service (QoS) can be significantly improved by smart combinations of scheduling policies.

Multipath connectivity and aggregation of multiple communication links is actively being researched with the aim to achieve higher throughput and lower latency. In this work we perform an emulation-based evaluation of the relative goodput of MPTCP and TCP in a 5G usage context. A large range of path capacity and delay conditions is explored, for both the primary and secondary paths, with over 2000 different configurations evaluated. Evaluations are performed over eight combinations of MPTCP schedulers and congestion controls. The results show that MPTCP running over two links provide lower goodput than TCP over a single link for the majority of cases. Asymmetry in link conditions is in many cases a major complication for the MPTCP scheduler. To examine the predictability of poor performance, and to obtain further insight on the structure of this phenomena, we perform regression modeling of the relative good put. In addition to the traditional approaches of Linear Regression and Random Forest, we also employ Sym-bolic Regression to obtain mathematical expressions capable of providing insight on the path conditions most contributing to poor MPTCP performance. Such regression expressions can be informative when evaluating different schedulers or link aggregation approaches.

Cellular networks are continuously evolving to allow improved throughput and low latency performance for applications. However, it has been shown that, due to buffer over-provisioning, TCP's standard loss-based congestion control algorithms (CCAs) can cause long delays in cellular networks. The QUIC transport protocol and the Bottleneck Bandwidth and Round-trip propagation time (BBR) congestion control are both proposed in response to shortcomings observed in TCP and loss-based CCAs. Despite its notable advantages, BBR can experience suboptimal delay performance in cellular networks due to one of its underlying design choices: the maximum bandwidth filter at the sender. In this work, we leverage QUIC's extensibility to enhance BBR. Instead of using the ACK rate observed at the sender side, we apply a more fitting delivery rate calculated at the receiver. Our 5G-trace-based emulation experiments in CloudLab suggest that our modified QUIC could significantly improve latency without any notable effect on the throughput: In particular, in some of our experiments, we observe up to 39% reduction of the round-trip time (RTT) with a worstcase throughput reduction of 2.7%.

Cellular networks have evolved to support high peak bitrates with low loss rates as observed by the higher layers. However, applications and services running over cellular networks are now facing other difficult congestion-related challenges, most notably a highly variable link capacity and bufferbloat. To overcome these issues and improve performance of network traffic in 4G/5G cellular networks, a number of in-network and end-to-end solutions have been proposed. Fairness between interacting congestion control algorithms (CCAs) has played an important role in the type of CCAs considered for research and deployment. The placement of content closer to the user and the allocation of per-user queues in cellular networks has increased the likelihood of a cellular access bottleneck and reduced the extent of flow interaction between multiple users. This has resulted in renewed interest in end-to-end CCAs for cellular networks by opening up room for research and exploration. In this work, we present end-to-end CCAs that target a high throughput and a low latency over highly variable network links, and classify them according to the way they address the congestion control. The work also discusses the deployability of the algorithms. In addition, we provide insights into possible future research directions, such as coping with a higher degree of variability, interaction of CCAs in a shared bottleneck, and avenues for synergized research, such as CCAs assisted by software defined networking and network function virtualization. We hope that this work will serve as a starting point for systematically navigating through the expanding number of cellular CCAs.

Internet traffic is comprised of data flows from various applications with unique traffic characteristics. For many cloud applications, end-to-end latency is a primary factor affecting the perceived user experience. As packet losses cause delays in the communication they impact user experience, making efficient handling of packet losses an important function of transport layer protocols. Multipath TCP (MPTCP) is a modification to TCP that enables simultaneous use of several paths for a TCP flow. MPTCP is known to improve throughput. However, the performance of MPTCP is not optimal when handling certain loss scenarios. Efficient packet loss recovery is thus important to achieve desirable flow completion times for interactive cloud-based applications. In this paper we evaluate the performance of MPTCP in handling tail losses using traffic traces from various cloud-based applications. Tail losses, losses that occur at the end of a flow or traffic burst, are particularly challenging from a latency perspective as they are difficult to detect and recover in a timely manner. Tail losses in TCP are handled by using a tail loss probe (TLP) mechanism which was adapted to MPTCP from TCP. We investigate the performance of TLP in MPTCP, comparing the standard implementation to a recently proposed, less conservative approach. Our experimental results show that a less conservative implementation of TLP performs significantly better than the standard implementation in handling tail losses, reducing the average burst completion time of cloud based applications when tail loss occurs by up to 50% in certain cases.

As WiFi grows ever more popular, airtime contention becomes an increasing problem. One way to alleviate this is through network policy enforcement. Unfortunately, WiFi lacks protocol support for configuring policies for its usage, and since network-wide coordination cannot generally be ensured, enforcing policy is challenging. However, as we have shown in previous work, an access point can influence the behaviour of connected devices by changing its scheduling of transmission opportunities, which can be used to achieve airtime fairness. In this work, we show that this mechanism can be extended to successfully enforce airtime usage policies in WiFi networks. We implement this as an extension our previous airtime fairness work, and present PoliFi, the resulting policy enforcement system. Our evaluation shows that PoliFi makes it possible to express a range of useful policies. These include prioritisation of specific devices; balancing groups of devices for sharing between different logical networks or network slices; and limiting groups of devices to implement guest networks or other low-priority services. We also show how these can be used to improve the performance of a real-world DASH video streaming application.

The demand for mobile communication is continuously increasing, and mobile devices are now the communication device of choice for many people. To guarantee connectivity and performance, mobile devices are typically equipped with multiple interfaces. To this end, exploiting multiple available interfaces is also a crucial aspect of the upcoming 5G standard for reducing costs, easing network management, and providing a good user experience. Multi-path protocols, such as multi-path TCP (MPTCP), can be used to provide performance optimization through load-balancing and resilience to coverage drops and link failures, however, they do not automatically guarantee better performance. For instance, low-latency communication has been proven hard to achieve when a device has network interfaces with asymmetric capacity and delay (e.g., LTE and WLAN). For multi-path communication, the data scheduler is vital to provide low latency, since it decides over which network interface to send individual data segments. In this paper, we focus on the MPTCP scheduler with the goal of providing a good user experience for latency-sensitive applications when interface quality is asymmetric. After an initial assessment of existing scheduling algorithms, we present two novel scheduling techniques: the block estimation (BLEST) scheduler and the shortest transmission time first (STTF) scheduler. BLEST and STTF are compared with existing schedulers in both emulated and real-world environments and are shown to reduce web object transmission times with up to 51% and provide 45% faster communication for interactive applications, compared with MPTCP's default scheduler.

Information-centric networking (ICN) with its design around named-based forwarding and in-network caching holds great promises to become a key architecture for the future Internet. Many proposed ICN hop-by-hop congestion control schemes assume a fixed and known link capacity, which rarely - if ever - holds true for wireless links. Firstly, we demonstrate that although these congestion control schemes are able to fairly well utilise the available wireless link capacity, they greatly fail to keep the delay low. In fact, they essentially offer the same delay as in the case with no hop-by-hop, only end-to-end, congestion control. Secondly, we show that by complementing these schemes with an easy-to-implement, packet-train capacity estimator, we reduce the delay to a level significantly lower than what is obtained with only end-to-end congestion control, while still being able to keep the link utilisation at a high level.

We analyse two complementary datasets to quantify the latency variation experienced by internet end-users: (i) a large-scale active measurement dataset (from the Measurement Lab Network Diagnostic Tool) which shed light on long-term trends and regional differences; and (ii) passive measurement data from an access aggregation link which is used to analyse the edge links closest to the user.

There is a growing concern that the Internet transport layer has become less adaptive to the requirements of new applications, and that further evolution has become very difficult. This is because a fundamental assumption no longer holds: it can no longer be assumed that the transport layer is only in the scope of end-hosts. The success of TCP and UDP and the ubiquity of middleboxes have led to ossification of both the network infrastructure and the API presented to applications. This has led to the development of workarounds and point solutions that fail to cover many facets of the problem. To address this issue, this paper identifies requirements for a new transport layer and then proposes a conceptual architecture that we argue is both flexible and evolvable. This new architecture requires that applications interface to the transport at a higher abstraction level, where an application can express communication preferences via a new richer API. Protocol machinery can use this information to decide which of the available transport protocols is used. By placing the protocol machinery in the transport layer, the new architecture can allow for new protocols to be deployed and enable evolution of the transport layer.

Several new active queue management (AQM) and hybrid AQM/fairness queueing algorithms have been proposed recently. They seek to ensure low queueing delay and high network goodput without requiring parameter tuning of the algorithms themselves. However, extensive experimental evaluations of these algorithms are still lacking. This paper evaluates a selection of bottleneck queue management schemes in a test-bed representative of residential Internet connections of both symmetrical and asymmetrical bandwidths as well as WiFi. Latency under load and the performance of VoIP and web traffic patterns are evaluated under steady state conditions. Furthermore, the impact of the algorithms on fairness between TCP flows with different RTTs, and also the transient behaviour of the algorithms at flow startup is examined. The results show that while the AQM algorithms can significantly improve steady state performance, they exacerbate TCP flow unfairness. In addition, the evaluated AQMs severely struggle to quickly control queueing latency at flow startup, which can lead to large latency spikes that hurt the perceived performance. The fairness queueing algorithms almost completely alleviate the algorithm performance problems, providing the best balance of low latency and high throughput in the tested scenarios. However, on WiFi the performance of all the tested algorithms is hampered by large amounts of queueing in lower layers of the network stack inducing significant latency outside of the algorithms’ control.

Internet-based applications that require low latency are becoming more common. Such applications typically generate traffic consisting of short, or bursty, TCP flows. As TCP, instead, is designed to optimize the throughput of long bulk flows there is an apparent mismatch. To overcome this, a lot of research has recently focused on optimizing TCP for short flows as well. In this paper, we identify a performance problem for short flows caused by the metric caching conducted by the TCP control block interdependence mechanisms. Using this metric caching, a single packet loss can potentially ruin the performance for all future flows to the same destination by making them start in congestion avoidance instead of slow-start. To solve this, we propose an enhanced selective caching mechanism for short flows. To illustrate the usefulness of our approach, we implement it in both Linux and FreeBSD and experimentally evaluate it in a real test-bed. The experiments show that the selective caching approach is able to reduce the average transmission time of short flows by up to 40%.

Routing packets over multiple disjoint paths towards a destination can increase network utilization by load-balancing the traffic over the network. In wireless mesh networks, multi-radio multi-channel nodes are often used to create a larger set of interference-free paths thus increasing the chance of load-balancing. The drawback of load-balancing is that different paths might have different delay properties, causing packets to be reordered. This can reduce TCP performance significantly, as reordering is interpreted as a sign of congestion. Packet reordering can be avoided by letting the network layer forward traffic strictly on flow-level. This would avoid the negative drawbacks of packet reordering, but will also limit the ability to achieve optimal network throughput. On the other hand, there are several proposals that try to mitigate the effects of reordering at the transport layer. In this paper, we perform an in-depth evaluation of such TCP reordering mitigations in multi-radio multi-channel wireless mesh networks when using multi-path forwarding. We evaluate two TCP reordering mitigation techniques implemented in the Linux kernel. The transport layer mitigations are compared using different multi-path forwarding strategies. Our findings show that, in general, flow-level forwarding gives the best TCP performance and that transport layer reordering mitigations only marginally can improve performance.

Routing packets over multiple disjoint paths towards a destination can increase network utilization by load-balancing the traffic over the network. The drawback of load-balancing is that different paths might have different delay properties, causing packets to be reordered. This can reduce TCP performance significantly, as reordering is interpreted as a sign of congestion. Packet reordering can be avoided by letting the network layer route strictly on flow-level. This will, however, also limit the ability to achieve optimal network throughput. There are also several proposals that try to mitigate the effects of reordering at the transport layer. In this paper, we perform an initial evaluation of such TCP reordering mitigations in multi-radio multi-channel wireless mesh networks when using multi-path routing. We evaluate two TCP reordering mitigation techniques implemented in the Linux kernel. The transport layer mitigations are compared using different multi-path routing strategies. Our findings show that, in general, flow-level routing gives the best TCP performance and that transport layer reordering mitigations only marginally can improve performance.

From being regarded as a pathological event, packet reordering is now considered to be naturally prevalent within the Internet. When packets are reordered, the performance of transport protocols like TCP can be severely hurt. To overcome performance problems a number of mitigations have been proposed. Common for most proposals is, however, the lack of evaluations using real protocol implementations and good models of packet reordering. In this paper we highlight the need for detailed reordering models, and implement support for such models in the KauNet network emulator. To demonstrate the importance of using detailed models we present an experimental example.

The Stream Control Transmission Protocol (SCTP) was designed by the IETF as a viable solution for transportation of signaling traffic within IP-based networks. Signaling traffic is different from ordinary TCP bulk traffic in many ways. One example is that the requirement of timely delivery usually is much stricter. However, the management of the SCTP retransmission timer is not optimally designed considering this requirement. Basically, the management algorithm, unnecessarily, extends the time needed for loss detection. This paper presents a new management algorithm that is able to maintain a correct state of the retransmission timer, which eliminates this particular problem. In addition, the paper also compares the performance of the two management algorithms in an emulated signaling environment, using the lksctp implementation of SCTP. The results show that the proposed algorithm is able to provide significant reductions in loss recovery time. In some cases, the time needed to recover from packet loss is reduced with as much as 43%.