An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions

Quality of service assessment and analysis of wireless multimedia networks.

Recent years have witnessed a vast technological progress in the area of Quality of Service (QoS), mainly due to the emergence of multimedia networking and computing. QoS measurement and analysis have long been of interest to the networking research community. The major goals of this thesis are of two fold: Firstly, to investigate the effect of the QoS parameters on the overall QoS experienced by wireless networks. Secondly, to utilise the results in developing efficient mechanisms for intrusive and non-intrusive assessments of the performance of wireless ad hoc networks as well as the measurement of the available QoS for audio and videoconferencing applications over the IEEE 802.11 standard. To evaluate the network performance and the overall QoS of multimedia applications, new fuzzy logic and distance measure assessment approaches were developed taking into account the QoS parameters requirements of each application. The developed approaches essentially include measuring the main QoS parameters (delay, jitter and packet loss) and use them as input to the measurement systems, which combine them and produce an output that represents the instantaneous QoS. The devised approaches showed how the QoS can be measured without a need for complicated analytical mathematical models.In this study, several techniques were devised for estimating QoS. Firstly, a probe-based assessment method (active technique) was developed. In this method, special artificial monitoring packets were injected into the network. The overall QoS and its parameters were estimated by collecting statistics from these packets. It was possible to make reasonable inferences about the delay, throughput, packet losses and the overall average QoS using different probe rates. This technique showed some limitations for measuring the jitter. In addition, the rate of the monitoring packets played an essential role in the precision, level of resolution of estimated results and negatively impacted the network performance. Secondly, to overcome some of the drawbacks of the probing-based method, a new assessment technique was, subsequently, devised based on passive monitoring standard sampling methods. Unlike the active technique, the new method has the advantage of not adding an extra load to the network. In addition, it is not like the typical passive methods, which require the transfer and calculations of the whole captured data. Generally, all sampling schemes provided satisfactory measures of the overall QoS and its parameters and produced very acceptable bias and Relative Standard Error (RSE) result. Systematic sampling provided the most accurate estimates compared to the stratified and random approaches. In addition, after sample fraction of 2%, the estimated overall QoS bias from the actual QoS became constant and equal to -0.5% and RSE was less than 0.005 using both fuzzy and distance assessment systems. Thirdly, in order to overcome some negative aspects of inaccuracy and biasness caused by sampling techniques, a new scheme was proposed to correct these results to be closer to the actual traffic measurements. The new approach does not disturb the network performance (as in active methods), neither depends on the whole traffic (as in passive methods), nor bias the actual results (as in the standard sampling technique). Similarly, systematic sampling showed the best performance. Sample fractions, using the systematic sampling, greater than 2% gave an overall estimated QoS identical to the actual QoS because the obtained relative error was nearly constant and approximately close to zero using both assessment systems. The measured QoS can be used to optimise the received quality of the multimedia services along with the changing network conditions and to manage the utilisation of the network available resources especially for ad hoc networks. Overall, the findings of this study contribute to a method for drawing a realistic picture of the wireless multimedia networks QoS and provide a firm basis and useful insights on how to effectively design future QoS solutions

Non-Intrusive Measurement in Packet Networks and its Applications

PhDNetwork measurementis becoming increasingly important as a meanst o assesst he performanceo f packet networks. Network performance can involve different aspects such as availability, link failure detection etc, but in this thesis, we will focus on Quality of Service (QoS). Among the metrics used to define QoS, we are particularly interested in end-to-end delay performance. Recently, the adoption of Service Level Agreements (SLA) between network operators and their customersh as becomea major driving force behind QoS measurementm: easurementi s necessaryt o produce evidence of fulfilment of the requirements specified in the SLA. Many attempts to do QoS based packet level measurement have been based on Active Measurement, in which the properties of the end-to-end path are tested by adding testing packets generated from the sending end. The main drawback of active probing is its intrusive nature which causes extraburden on the network, and has been shown to distort the measured condition of the network. The other category of network measurement is known as Passive Measurement. In contrast to Active Measurement, there are no testing packets injected into the network, therefore no intrusion is caused. The proposed applications using Passive Measurement are currently quite limited. But Passive Measurement may offer the potential for an entirely different perspective compared with Active Measurements In this thesis, the objective is to develop a measurement methodology for the end-to-end delay performance based on Passive Measurement. We assume that the nodes in a network domain are accessible.F or example, a network domain operatedb y a single network operator. The novel idea is to estimate the local per-hop delay distribution based on a hybrid approach (model and measurement-based)W. ith this approach,t he storagem easurementd ata requirement can be greatly alleviated and the overhead put in each local node can be minimized, so maintaining the fast switching operation in a local switcher or router. Per-hop delay distributions have been widely used to infer QoS at a single local node. However, the end-to-end delay distribution is more appropriate when quantifying delays across an end-to-end path. Our approach is to capture every local node's delay distribution, and then the end-to-end delay distribution can be obtained by convolving the estimated delay distributions. In this thesis, our algorithm is examined by comparing the proximity of the actual end-to-end delay distribution with the estimated one obtained by our measurement method under various conditions. e. g. in the presence of Markovian or Power-law traffic. Furthermore, the comparison between Active Measurement and our scheme is also studied. 2 Network operators may find our scheme useful when measuring the end-to-end delay performance. As stated earlier, our scheme has no intrusive effect. Furthermore, the measurement result in the local node can be re-usable to deduce other paths' end-to-end delay behaviour as long as this local node is included in the path. Thus our scheme is more scalable compared with active probing

Packet level measurement over wireless access

PhDPerformance Measurement of the IP packet networks mainly comprise of monitoring the network performance in terms of packet losses and delays. If used appropriately, these network parameters (i.e. delay, loss and bandwidth etc) can indicate the performance status of the network and they can be used in fault and performance monitoring, network provisioning, and traffic engineering. Globally, there is a growing need for accurate network measurement to support the commercial use of IP networks. In wireless networks, transmission losses and communication delays strongly affect the performance of the network. Compared to wired networks, wireless networks experience higher levels of data dropouts, and corruption due to issues of channel fading, noise, interference and mobility. Performance monitoring is a vital element in the commercial future of broadband packet networking and the ability to guarantee quality of service in such networks is implicit in Service Level Agreements. Active measurements are performed by injecting probes, and this is widely used to determine the end to end performance. End to end delay in wired networks has been extensively investigated, and in this thesis we report on the accuracy achieved by probing for end to end delay over a wireless scenario. We have compared two probing techniques i.e. Periodic and Poisson probing, and estimated the absolute error for both. The simulations have been performed for single hop and multi- hop wireless networks. In addition to end to end latency, Active measurements have also been performed for packet loss rate. The simulation based analysis has been tried under different traffic scenarios using Poisson Traffic Models. We have sampled the user traffic using Periodic probing at different rates for single hop and multiple hop wireless scenarios. 5 Active probing becomes critical at higher values of load forcing the network to saturation much earlier. We have evaluated the impact of monitoring overheads on the user traffic, and show that even small amount of probing overhead in a wireless medium can cause large degradation in network performance. Although probing at high rate provides a good estimation of delay distribution of user traffic with large variance yet there is a critical tradeoff between the accuracy of measurement and the packet probing overhead. Our results suggest that active probing is highly affected by probe size, rate, pattern, traffic load, and nature of shared medium, available bandwidth and the burstiness of the traffic

QoE-Based Low-Delay Live Streaming Using Throughput Predictions

Recently, HTTP-based adaptive streaming has become the de facto standard for video streaming over the Internet. It allows clients to dynamically adapt media characteristics to network conditions in order to ensure a high quality of experience, that is, minimize playback interruptions, while maximizing video quality at a reasonable level of quality changes. In the case of live streaming, this task becomes particularly challenging due to the latency constraints. The challenge further increases if a client uses a wireless network, where the throughput is subject to considerable fluctuations. Consequently, live streams often exhibit latencies of up to 30 seconds. In the present work, we introduce an adaptation algorithm for HTTP-based live streaming called LOLYPOP (Low-Latency Prediction-Based Adaptation) that is designed to operate with a transport latency of few seconds. To reach this goal, LOLYPOP leverages TCP throughput predictions on multiple time scales, from 1 to 10 seconds, along with an estimate of the prediction error distribution. In addition to satisfying the latency constraint, the algorithm heuristically maximizes the quality of experience by maximizing the average video quality as a function of the number of skipped segments and quality transitions. In order to select an efficient prediction method, we studied the performance of several time series prediction methods in IEEE 802.11 wireless access networks. We evaluated LOLYPOP under a large set of experimental conditions limiting the transport latency to 3 seconds, against a state-of-the-art adaptation algorithm from the literature, called FESTIVE. We observed that the average video quality is by up to a factor of 3 higher than with FESTIVE. We also observed that LOLYPOP is able to reach a broader region in the quality of experience space, and thus it is better adjustable to the user profile or service provider requirements.Comment: Technical Report TKN-16-001, Telecommunication Networks Group, Technische Universitaet Berlin. This TR updated TR TKN-15-00

An Overview of Internet Measurements:Fundamentals, Techniques, and Trends

The Internet presents great challenges to the characterization of its structure and behavior. Different reasons contribute to this situation, including a huge user community, a large range of applications, equipment heterogeneity, distributed administration, vast geographic coverage, and the dynamism that are typical of the current Internet. In order to deal with these challenges, several measurement-based approaches have been recently proposed to estimate and better understand the behavior, dynamics, and properties of the Internet. The set of these measurement-based techniques composes the Internet Measurements area of research. This overview paper covers the Internet Measurements area by presenting measurement-based tools and methods that directly influence other conventional areas, such as network design and planning, traffic engineering, quality of service, and network management

Prediction-based techniques for the optimization of mobile networks

Mención Internacional en el título de doctorMobile cellular networks are complex system whose behavior is characterized by the superposition of several random phenomena, most of which, related to human activities, such as mobility, communications and network usage. However, when observed in their totality, the many individual components merge into more deterministic patterns and trends start to be identifiable and predictable. In this thesis we analyze a recent branch of network optimization that is commonly referred to as anticipatory networking and that entails the combination of prediction solutions and network optimization schemes. The main intuition behind anticipatory networking is that knowing in advance what is going on in the network can help understanding potentially severe problems and mitigate their impact by applying solution when they are still in their initial states. Conversely, network forecast might also indicate a future improvement in the overall network condition (i.e. load reduction or better signal quality reported from users). In such a case, resources can be assigned more sparingly requiring users to rely on buffered information while waiting for the better condition when it will be more convenient to grant more resources. In the beginning of this thesis we will survey the current anticipatory networking panorama and the many prediction and optimization solutions proposed so far. In the main body of the work, we will propose our novel solutions to the problem, the tools and methodologies we designed to evaluate them and to perform a real world evaluation of our schemes. By the end of this work it will be clear that not only is anticipatory networking a very promising theoretical framework, but also that it is feasible and it can deliver substantial benefit to current and next generation mobile networks. In fact, with both our theoretical and practical results we show evidences that more than one third of the resources can be saved and even larger gain can be achieved for data rate enhancements.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Albert Banchs Roca.- Presidente: Pablo Serrano Yañez-Mingot.- Secretario: Jorge Ortín Gracia.- Vocal: Guevara Noubi

Optimizing the delivery of multimedia over mobile networks

Mención Internacional en el título de doctorThe consumption of multimedia content is moving from a residential environment to mobile phones. Mobile data traffic, driven mostly by video demand, is increasing rapidly and wireless spectrum is becoming a more and more scarce resource. This makes it highly important to operate mobile networks efficiently. To tackle this, recent developments in anticipatory networking schemes make it possible to to predict the future capacity of mobile devices and optimize the allocation of the limited wireless resources. Further, optimizing Quality of Experience—smooth, quick, and high quality playback—is more difficult in the mobile setting, due to the highly dynamic nature of wireless links. A key requirement for achieving, both anticipatory networking schemes and QoE optimization, is estimating the available bandwidth of mobile devices. Ideally, this should be done quickly and with low overhead. In summary, we propose a series of improvements to the delivery of multimedia over mobile networks. We do so, be identifying inefficiencies in the interconnection of mobile operators with the servers hosting content, propose an algorithm to opportunistically create frequent capacity estimations suitable for use in resource optimization solutions and finally propose another algorithm able to estimate the bandwidth class of a device based on minimal traffic in order to identify the ideal streaming quality its connection may support before commencing playback. The main body of this thesis proposes two lightweight algorithms designed to provide bandwidth estimations under the high constraints of the mobile environment, such as and most notably the usually very limited traffic quota. To do so, we begin with providing a thorough overview of the communication path between a content server and a mobile device. We continue with analysing how accurate smartphone measurements can be and also go in depth identifying the various artifacts adding noise to the fidelity of on device measurements. Then, we first propose a novel lightweight measurement technique that can be used as a basis for advanced resource optimization algorithms to be run on mobile phones. Our main idea leverages an original packet dispersion based technique to estimate per user capacity. This allows passive measurements by just sampling the existing mobile traffic. Our technique is able to efficiently filter outliers introduced by mobile network schedulers and phone hardware. In order to asses and verify our measurement technique, we apply it to a diverse dataset generated by both extensive simulations and a week-long measurement campaign spanning two cities in two countries, different radio technologies, and covering all times of the day. The results demonstrate that our technique is effective even if it is provided only with a small fraction of the exchanged packets of a flow. The only requirement for the input data is that it should consist of a few consecutive packets that are gathered periodically. This makes the measurement algorithm a good candidate for inclusion in OS libraries to allow for advanced resource optimization and application-level traffic scheduling, based on current and predicted future user capacity. We proceed with another algorithm that takes advantage of the traffic generated by short-lived TCP connections, which form the majority of the mobile connections, to passively estimate the currently available bandwidth class. Our algorithm is able to extract useful information even if the TCP connection never exits the slow start phase. To the best of our knowledge, no other solution can operate with such constrained input. Our estimation method is able to achieve good precision despite artifacts introduced by the slow start behavior of TCP, mobile scheduler and phone hardware. We evaluate our solution against traces collected in 4 European countries. Furthermore, the small footprint of our algorithm allows its deployment on resource limited devices. Finally, in an attempt to face the rapid traffic increase, mobile application developers outsource their cloud infrastructure deployment and content delivery to cloud computing services and content delivery networks. Studying how these services, which we collectively denote Cloud Service Providers (CSPs), perform over Mobile Network Operators (MNOs) is crucial to understanding some of the performance limitations of today’s mobile apps. To that end, we perform the first empirical study of the complex dynamics between applications, MNOs and CSPs. First, we use real mobile app traffic traces that we gathered through a global crowdsourcing campaign to identify the most prevalent CSPs supporting today’s mobile Internet. Then, we investigate how well these services interconnect with major European MNOs at a topological level, and measure their performance over European MNO networks through a month-long measurement campaign on the MONROE mobile broadband testbed. We discover that the top 6 most prevalent CSPs are used by 85% of apps, and observe significant differences in their performance across different MNOs due to the nature of their services, peering relationships with MNOs, and deployment strategies. We also find that CSP performance in MNOs is affected by inflated path length, roaming, and presence of middleboxes, but not influenced by the choice of DNS resolver. We also observe that the choice of operator’s Point of Presence (PoP) may inflate by at least 20% the delay towards popular websites.This work has been supported by IMDEA Networks Institute.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Ahmed Elmokashfi.- Secretario: Rubén Cuevas Rumín.- Vocal: Paolo Din

Cooperative control of relay based cellular networks

PhDThe increasing popularity of wireless communications and the higher data requirements of new types of service lead to higher demands on wireless networks. Relay based cellular networks have been seen as an effective way to meet users’ increased data rate requirements while still retaining the benefits of a cellular structure. However, maximizing the probability of providing service and spectrum efficiency are still major challenges for network operators and engineers because of the heterogeneous traffic demands, hard-to-predict user movements and complex traffic models. In a mobile network, load balancing is recognised as an efficient way to increase the utilization of limited frequency spectrum at reasonable costs. Cooperative control based on geographic load balancing is employed to provide flexibility for relay based cellular networks and to respond to changes in the environment. According to the potential capability of existing antenna systems, adaptive radio frequency domain control in the physical layer is explored to provide coverage at the right place at the right time. This thesis proposes several effective and efficient approaches to improve spectrum efficiency using network wide optimization to coordinate the coverage offered by different network components according to the antenna models and relay station capability. The approaches include tilting of antenna sectors, changing the power of omni-directional antennas, and changing the assignment of relay stations to different base stations. Experiments show that the proposed approaches offer significant improvements and robustness in heterogeneous traffic scenarios and when the propagation environment changes. The issue of predicting the consequence of cooperative decisions regarding antenna configurations when applied in a realistic environment is described, and a coverage prediction model is proposed. The consequences of applying changes to the antenna configuration on handovers are analysed in detail. The performance evaluations are based on a system level simulator in the context of Mobile WiMAX technology, but the concepts apply more generally