Modeling and analysis of LTE connectivity in a high mobility vehicular environment

Long-Term Evolution (LTE) technology has several features that make it an attractive alternative to be used in vehicle-to-infrastructure communications for intelligent transportation systems. However, before LTE can be widely used in this context, a number of analyses must provide convincing evidence that critical network functions (e.g. resource allocation strategies) yield adequate performance. To this end, in this work, we introduce a Markov-chain based model for LTE downlink channel quality, a prime factor affecting performance. Our model comes from the analysis of a large number of measurements of LTE Cell-Specific Reference Signals that were collected through a crowdsourcing application on a motorway in the UK. The model is intended to be used in performance evaluation studies and we exemplify its use with a case study, where we estimate the downlink transmission capacity of an LTE network. We also discuss other potential applications

Análisis del comportamiento de BBR en redes 4G

BBR es un nuevo algoritmo de control de congestión desarrollado por Google. A diferencia de los protocolos tradicionales que se basan en la pérdida de paquetes como señal de congestión, BBR estima la capacidad del canal disponible para determinar la cantidad de datos que enviar. BBR trata de mejorar el uso del canal evitando la creación de colas en los enlaces de menor capacidad. En la publicación original de BBR se muestra un mejor rendimiento en topologías estáticas frente a TCP CUBIC. Ante la falta de información acerca de cómo se comporta en entornos móviles, este proyecto trata de evaluar el rendimiento de BBR en redes LTE.BBR is a new congestion control algorithm developed by Google. Instead of using packet loss as congestion signal, like many currently used congestion control algorithms, BBR estimates the available bandwith in bottleneck links in order to determinate its sending rate. It tries to provide high link utilization while avoiding queues creation in bottleneck buffers. The original publication of BBR shows that it can deliver superior performance in static environments compared to CUBIC TCP. In the absence of information about how it behaves in mobile environments, this project tries to evaluate the performance of BBR in LTE networks.BBR Googlek garatutako kongestio kontrol algoritmo berria da. Kongestio seinale bezala paketeen galeran oinarritzen diren ohiko protokoloak ez bezala, BBR-k kanal erabilgarriaren gaitasuna estimatzen du, bidaliko den datu kantitatea zehazteko. BBR kanalaren erabilera hobetzen saiatzen da, gaitasun txikiko loturetan ilaren sorkuntza saihestuz. BBR-ren argitalpen originalak erakusten du, topologia estatikoan, TCP CUBIC bezalako ohiko protokoloen aurrean errendimendu hobeagoa duela. Ingurune mugikorretan BBR-ren portaerari buruzko informazio falta dela eta, proiektu honek, BBR-ren errendimendua LTE sareetan ebaluatzen ahalegintzen da

Non-stationary service curves : model and estimation method with application to cellular sleep scheduling

In today’s computer networks, short-lived flows are predominant. Consequently, transient start-up effects such as the connection establishment in cellular networks have a significant impact on the performance. Although various solutions are derived in the fields of queuing theory, available bandwidths, and network calculus, the focus is, e.g., about the mean wake-up times, estimates of the available bandwidth, which consist either out of a single value or a stationary function and steady-state solutions for backlog and delay. Contrary, the analysis during transient phases presents fundamental challenges that have only been partially solved and is therefore understood to a much lesser extent. To better comprehend systems with transient characteristics and to explain their behavior, this thesis contributes a concept of non-stationary service curves that belong to the framework of stochastic network calculus. Thereby, we derive models of sleep scheduling including time-variant performance bounds for backlog and delay. We investigate the impact of arrival rates and different duration of wake-up times, where the metrics of interest are the transient overshoot and relaxation time. We compare a time-variant and a time-invariant description of the service with an exact solution. To avoid probabilistic and maybe unpredictable effects from random services, we first choose a deterministic description of the service and present results that illustrate that only the time-variant service curve can follow the progression of the exact solution. In contrast, the time-invariant service curve remains in the worst-case value. Since in real cellular networks, it is well known that the service and sleep scheduling procedure is random, we extend the theory to the stochastic case and derive a model with a non-stationary service curve based on regenerative processes. Further, the estimation of cellular network’s capacity/ available bandwidth from measurements is an important topic that attracts research, and several works exist that obtain an estimate from measurements. Assuming a system without any knowledge about its internals, we investigate existing measurement methods such as the prevalent rate scanning and the burst response method. We find fundamental limitations to estimate the service accurately in a time-variant way, which can be explained by the non-convexity of transient services and their super-additive network processes. In order to overcome these limitations, we derive a novel two-phase probing technique. In the first step, the shape of a minimal probe is identified, which we then use to obtain an accurate estimate of the unknown service. To demonstrate the minimal probing method’s applicability, we perform a comprehensive measurement campaign in cellular networks with sleep scheduling (2G, 3G, and 4G). Here, we observe significant transient backlogs and delay overshoots that persist for long relaxation times by sending constant-bit-rate traffic, which matches the findings from our theoretical model. Contrary, the minimal probing method shows another strength: sending the minimal probe eliminates the transient overshoots and relaxation times

Doctor of Philosophy

dissertationThe next generation mobile network (i.e., 5G network) is expected to host emerging use cases that have a wide range of requirements; from Internet of Things (IoT) devices that prefer low-overhead and scalable network to remote machine operation or remote healthcare services that require reliable end-to-end communications. Improving scalability and reliability is among the most important challenges of designing the next generation mobile architecture. The current (4G) mobile core network heavily relies on hardware-based proprietary components. The core networks are expensive and therefore are available in limited locations in the country. This leads to a high end-to-end latency due to the long latency between base stations and the mobile core, and limitations in having innovations and an evolvable network. Moreover, at the protocol level the current mobile network architecture was designed for a limited number of smart-phones streaming a large amount of high quality traffic but not a massive number of low-capability devices sending small and sporadic traffic. This results in high-overhead control and data planes in the mobile core network that are not suitable for a massive number of future Internet-of-Things (IoT) devices. In terms of reliability, network operators already deployed multiple monitoring sys- tems to detect service disruptions and fix problems when they occur. However, detecting all service disruptions is challenging. First, there is a complex relationship between the network status and user-perceived service experience. Second, service disruptions could happen because of reasons that are beyond the network itself. With technology advancements in Software-defined Network (SDN) and Network Func- tion Virtualization (NFV), the next generation mobile network is expected to be NFV-based and deployed on NFV platforms. However, in contrast to telecom-grade hardware with built-in redundancy, commodity off-the-shell (COTS) hardware in NFV platforms often can't be comparable in term of reliability. Availability of Telecom-grade mobile core network hardwares is typically 99.999% (i.e., "five-9s" availability) while most NFV platforms only guarantee "three-9s" availability - orders of magnitude less reliable. Therefore, an NFV-based mobile core network needs extra mechanisms to guarantee its availability. This Ph.D. dissertation focuses on using SDN/NFV, data analytics and distributed system techniques to enhance scalability and reliability of the next generation mobile core network. The dissertation makes the following contributions. First, it presents SMORE, a practical offloading architecture that reduces end-to-end latency and enables new functionalities in mobile networks. It then presents SIMECA, a light-weight and scalable mobile core network designed for a massive number of future IoT devices. Second, it presents ABSENCE, a passive service monitoring system using customer usage and data analytics to detect silent failures in an operational mobile network. Lastly, it presents ECHO, a distributed mobile core network architecture to improve availability of NFV-based mobile core network in public clouds

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

Ph.DDOCTOR OF PHILOSOPH

An end-to-end measurement study of modern cellular data networks

10.1007/978-3-319-04918-2-4Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)8362 LNCS34-4