Buffer De-bloating in Wireless Access Networks

PhDExcessive buffering brings a new challenge into the networks which is known as Bufferbloat, which is harmful to delay sensitive applications. Wireless access networks consist of Wi-Fi and cellular networks. In the thesis, the performance of CoDel and RED are investigated in Wi-Fi networks with different types of traffic. Results show that CoDel and RED work well in Wi-Fi networks, due to the similarity of protocol structures of Wi-Fi and wired networks. It is difficult for RED to tune parameters in cellular networks because of the time-varying channel. CoDel needs modifications as it drops the first packet of queue and the head packet in cellular networks will be segmented. The major contribution of this thesis is that three new AQM algorithms tailored to cellular networks are proposed to alleviate large queuing delays. A channel quality aware AQM is proposed using the CQI. The proposed algorithm is tested with a single cell topology and simulation results show that the proposed algorithm reduces the average queuing delay for each user by 40% on average with TCP traffic compared to CoDel. A QoE aware AQM is proposed for VoIP traffic. Drops and delay are monitored and turned into QoE by mathematical models. The proposed algorithm is tested in NS3 and compared with CoDel, and it enhances the QoE of VoIP traffic and the average endto- end delay is reduced by more than 200 ms when multiple users with different CQI compete for the wireless channel. A random back-off AQM is proposed to alleviate the queuing delay created by video in cellular networks. The proposed algorithm monitors the play-out buffer and postpones the request of the next packet. The proposed algorithm is tested in various scenarios and it outperforms CoDel by 18% in controlling the average end-to-end delay when users have different channel conditions

A Multifaceted Look at Starlink Performance

In recent years, Low-Earth Orbit (LEO) mega-constellations have emerged as a promising network technology and have ushered in a new era for democratizing Internet access. The Starlink network from SpaceX stands out as the only consumer-facing LEO network with over 2M+ customers and more than 4000 operational satellites. In this paper, we conduct the first-of-its-kind extensive multi-faceted analysis of Starlink network performance leveraging several measurement sources. First, based on 19.2M crowdsourced M-Lab speed test measurements from 34 countries since 2021, we analyze Starlink global performance relative to terrestrial cellular networks. Second, we examine Starlink's ability to support real-time web-based latency and bandwidth-critical applications by analyzing the performance of (i) Zoom video conferencing, and (ii) Luna cloud gaming, comparing it to 5G and terrestrial fiber. Third, we orchestrate targeted measurements from Starlink-enabled RIPE Atlas probes to shed light on the last-mile Starlink access and other factors affecting its performance globally. Finally, we conduct controlled experiments from Starlink dishes in two countries and analyze the impact of globally synchronized "15-second reconfiguration intervals" of the links that cause substantial latency and throughput variations. Our unique analysis provides revealing insights on global Starlink functionality and paints the most comprehensive picture of the LEO network's operation to date.Comment: In submissio

A Simple Non-Deterministic Approach Can Adapt to Complex Unpredictable 5G Cellular Networks

5G cellular networks are envisioned to support a wide range of emerging delay-oriented services with different delay requirements (e.g., 20ms for VR/AR, 40ms for cloud gaming, and 100ms for immersive video streaming). However, due to the highly variable and unpredictable nature of 5G access links, existing end-to-end (e2e) congestion control (CC) schemes perform poorly for them. In this paper, we demonstrate that properly blending non-deterministic exploration techniques with straightforward proactive and reactive measures is sufficient to design a simple yet effective e2e CC scheme for 5G networks that can: (1) achieve high controllable performance, and (2) possess provable properties. To that end, we designed Reminis and through extensive experiments on emulated and real-world 5G networks, show the performance benefits of it compared with different CC schemes. For instance, averaged over 60 different 5G cellular links on the Standalone (SA) scenarios, compared with a recent design by Google (BBR2), Reminis can achieve 2.2x lower 95th percentile delay while having the same link utilization

A Rate-based TCP Congestion Control Framework for Cellular Data Networks

Ph.DDOCTOR OF PHILOSOPH

Incast mitigation in a data center storage cluster through a dynamic fair-share buffer policy

Incast is a phenomenon when multiple devices interact with only one device at a given time. Multiple storage senders overflow either the switch buffer or the single-receiver memory. This pattern causes all concurrent-senders to stop and wait for buffer/memory availability, and leads to a packet loss and retransmission—resulting in a huge latency. We present a software-defined technique tackling the many-to-one communication pattern—Incast—in a data center storage cluster. Our proposed method decouples the default TCP windowing mechanism from all storage servers, and delegates it to the software-defined storage controller. The proposed method removes the TCP saw-tooth behavior, provides a global flow awareness, and implements the dynamic fair-share buffer policy for end-to-end I/O path. It considers all I/O stages (applications, device drivers, NICs, switches/routers, file systems, I/O schedulers, main memory, and physical disks) while achieving the maximum I/O throughput. The policy, which is part of the proposed method, allocates fair-share bandwidth utilization for all storage servers. Priority queues are incorporated to handle the most important data flows. In addition, the proposed method provides better manageability and maintainability compared with traditional storage networks, where data plane and control plane reside in the same device

Contribution to reliable end-to-end communication over 5G networks using advanced techniques

5G cellular communication, especially with its hugely available bandwidth provided by millimeter-wave, is a promising technology to fulfill the coming high demand for vast data rates. These networks can support new use cases such as Vehicle to Vehicle and augmented reality due to its novel features such as network slicing along with the mmWave multi-gigabit-persecond data rate. Nevertheless, 5G cellular networks suffer from some shortcomings, especially in high frequencies because of the intermittent nature of channels when the frequency rises. Non-line of sight state is one of the significant issues that the new generation encounters. This drawback is because of the intense susceptibility of higher frequencies to blockage caused by obstacles and misalignment. This unique characteristic can impair the performance of the reliable transport layer widely deployed protocol, TCP, in attaining high throughput and low latency throughout a fair network. As a result, the protocol needs to adjust the congestion window size based on the current situation of the network. However, TCP cannot adjust its congestion window efficiently, which leads to throughput degradation of the protocol. This thesis presents a comprehensive analysis of reliable end-to-end communications in 5G networks and analyzes TCP’s behavior in one of the 3GPP’s well-known s cenarios called urban deployment. Furtherm ore, two novel TCPs bas ed on artificial intelligence have been proposed to deal with this issue. The first protocol uses Fuzzy logic, a subset of artificial intelligence, and the second one is based on deep learning. The extensively conducted simulations showed that the newly proposed protocols could attain higher performance than common TCPs, such as BBR, HighSpeed, Cubic, and NewReno in terms of throughput, RTT, and sending rate adjustment in the urban scenario. The new protocols' superiority is achieved by employing smartness in the conges tions control mechanism of TCP, which is a powerful enabler in fos tering TCP’s functionality. To s um up, the 5G network is a promising telecommunication infrastructure that will revolute various aspects of communication. However, different parts of the Internet, such as its regulations and protocol stack, will face new challenges, which need to be solved in order to exploit 5G capacity, and without intelligent rules and protocols, the high bandwidth of 5G, especially 5G mmWave will be wasted. Two novel schemes to solve the issues have been proposed based on an Artificial Intelligence subset technique called fuzzy and a machine learning-based approach called Deep learning to enhance the performance of 5G mmWave by improving the functionality of the transport layer. The obtained results indicated that the new schemes could improve the functionality of TCP by giving intelligence to the protocol. As the protocol works more smartly, it can make sufficient decisions on different conditions.La comunicació cel·lular 5G, especialment amb l’amplada de banda molt disponible que proporciona l’ona mil·limètrica, és una tecnologia prometedora per satisfer l’elevada demanda de grans velocitats de dades. Aquestes xarxes poden admetre casos d’ús nous, com ara Vehicle to Vehicle i realitat augmentada, a causa de les seves novetats, com ara el tall de xarxa juntament amb la velocitat de dades mWave de multi-gigabit per segon. Tot i això, les xarxes cel·lulars 5G pateixen algunes deficiències, sobretot en freqüències altes a causa de la naturalesa intermitent dels canals quan augmenta la freqüència. L’estat de no visió és un dels problemes significatius que troba la nova generació. Aquest inconvenient es deu a la intensa susceptibilitat de freqüències més altes al bloqueig causat per obstacles i desalineació. Aquesta característica única pot perjudicar el rendiment del protocol TCP, àmpliament desplegat, de capa de transport fiable en aconseguir un alt rendiment i una latència baixa en tota una xarxa justa. Com a resultat, el protocol ha d’ajustar la mida de la finestra de congestió en funció de la situació actual de la xarxa. Tot i això, TCP no pot ajustar la seva finestra de congestió de manera eficient, cosa que provoca una degradació del rendiment del protocol. Aquesta tesi presenta una anàlisi completa de comunicacions extrem a extrem en xarxes 5G i analitza el comportament de TCP en un dels escenaris coneguts del 3GPP anomenat desplegament urbà. A més, s'han proposat dos TCP nous basats en intel·ligència artificial per tractar aquest tema. El primer protocol utilitza la lògica Fuzzy, un subconjunt d’intel·ligència artificial, i el segon es basa en l’aprenentatge profund. Les simulacions àmpliament realitzades van mostrar que els protocols proposats recentment podrien assolir un rendiment superior als TCP habituals, com ara BBR, HighSpeed, Cubic i NewReno, en termes de rendiment, RTT i ajust d’índex d’enviament en l’escenari urbà. La superioritat dels nous protocols s’aconsegueix utilitzant la intel·ligència en el mecanisme de control de congestions de TCP, que és un poderós facilitador per fomentar la funcionalitat de TCP. En resum, la xarxa 5G és una prometedora infraestructura de telecomunicacions que revolucionarà diversos aspectes de la comunicació. No obstant això, diferents parts d’Internet, com ara les seves regulacions i la seva pila de protocols, s’enfrontaran a nous reptes, que cal resoldre per explotar la capacitat 5G, i sens regles i protocols intel·ligents, l’amplada de banda elevada de 5G, especialment 5G mmWave, pot ser desaprofitat. S'han proposat dos nous es quemes per resoldre els problemes basats en una tècnica de subconjunt d'Intel·ligència Artificial anomenada “difusa” i un enfocament basat en l'aprenentatge automàtic anomenat “Aprenentatge profund” per millorar el rendiment de 5G mmWave, millorant la funcionalitat de la capa de transport. Els resultats obtinguts van indicar que els nous esquemes podrien millorar la funcionalitat de TCP donant intel·ligència al protocol. Com que el protocol funciona de manera més intel·ligent, pot prendre decisions suficients en diferents condicionsPostprint (published version