Datacenter Traffic Control: Understanding Techniques and Trade-offs

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

Exploiting the power of multiplicity: a holistic survey of network-layer multipath

The Internet is inherently a multipath network: For an underlying network with only a single path, connecting various nodes would have been debilitatingly fragile. Unfortunately, traditional Internet technologies have been designed around the restrictive assumption of a single working path between a source and a destination. The lack of native multipath support constrains network performance even as the underlying network is richly connected and has redundant multiple paths. Computer networks can exploit the power of multiplicity, through which a diverse collection of paths is resource pooled as a single resource, to unlock the inherent redundancy of the Internet. This opens up a new vista of opportunities, promising increased throughput (through concurrent usage of multiple paths) and increased reliability and fault tolerance (through the use of multiple paths in backup/redundant arrangements). There are many emerging trends in networking that signify that the Internet's future will be multipath, including the use of multipath technology in data center computing; the ready availability of multiple heterogeneous radio interfaces in wireless (such as Wi-Fi and cellular) in wireless devices; ubiquity of mobile devices that are multihomed with heterogeneous access networks; and the development and standardization of multipath transport protocols such as multipath TCP. The aim of this paper is to provide a comprehensive survey of the literature on network-layer multipath solutions. We will present a detailed investigation of two important design issues, namely, the control plane problem of how to compute and select the routes and the data plane problem of how to split the flow on the computed paths. The main contribution of this paper is a systematic articulation of the main design issues in network-layer multipath routing along with a broad-ranging survey of the vast literature on network-layer multipathing. We also highlight open issues and identify directions for future work

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

Challenges on the way of implementing TCP over 5G networks

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-per-second 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 is not able to adjust its congestion window efficiently, and it leads to throughput degradation of the protocol. This paper presents a comprehensive analysis of reliable end-to-end communications in 5G networks. It provides the analysis of the effects of TCP in 5G mmWave networks, the discussion of TCP mechanisms and parameters involved in the performance over 5G networks, and a survey of current challenges, solutions, and proposals. Finally, a feasibility analysis proposal of machine learning-based approaches to improve reliable end-to-end communications in 5G networks is presented.This work was supported by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya under Grant 2017 SGR 376.Peer ReviewedPostprint (published version

Beyond socket options: making the Linux TCP stack truly extensible

The Transmission Control Protocol (TCP) is one of the most important protocols in today's Internet. Its specification and implementations have been refined for almost forty years. The Linux TCP stack is one of the most widely used TCP stacks given its utilisation on servers and Android smartphones and tablets. However, TCP and its implementations evolve very slowly. In this paper, we demonstrate how to leverage the eBPF virtual machine that is part of the recent versions of the Linux kernel to make the TCP stack easier to extend. We demonstrate a variety of use cases where the eBPF code is injected inside a running kernel to update or tune the TCP implementation. We first implement the TCP User Timeout Option. Then we propose a new option that enables a client to request a server to use a specific congestion control scheme. Our third extension is a TCP option that sets the initial congestion window. We then demonstrate how eBPF code can be used to tune the acknowledgment strategy.Comment: 9 pages, 8 figure