Open Access
Validation of HTTP response time from network traffic as an alternative to web browser instrumentation
(IEEE, 2021) López Romera, Carlos; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; Izal Azcárate, Mikel; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
The measurement of response time in hypertext transfer protocol (HTTP) requests is the most basic proxy measurement method for evaluating web browsing quality. It is used in the research literature and in application performance measurement instruments. During the development of a website, response time is obtained from in-browser measurements. After the website has been deployed, network traffic is used to continuously monitor activity, and the measurement data are used for service management and planning. In this study, we evaluate the accuracy of the measurements obtained from network traffic by comparing them with the in-browser measurement of resource load time. We evaluate the response times for encrypted and clear-text requests in an emulated network environment, in a laboratory deployment equivalent to a data centre network, and accessing popular web sites on the public Internet. The accuracy for response time measurements obtained from network traffic is noticeable higher for Internet long distance paths than for lowdelay paths (below 20 ms round-trip). The overhead of traffic encryption in secure HTTP requests has a negative effect on measurement accuracy, and we find relative measurement errors higher than 70% when using network traffic to infer HTTP response times compared
Open Access
Evaluation of RTT as an estimation of interactivity time for QoE evaluation in remote desktop environments
(IEEE, 2023) Arellano Usón, Jesús; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; Izal Azcárate, Mikel; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza
In recent years, there has been a notable surge in the utilization of remote desktop services, largely driven by the emergence of new remote work models introduced during the pandemic. Traditional evaluation of the quality of experience (QoE) of users in remote desktop environments has relied on measures such as round-trip time (RTT). However, these measures are insufficient to capture all the factors that influence QoE. This study evaluated RTT and interactivity time in an enterprise environment over a period of 6 months and analysed the suitability of using RTT drawing previously unexplored connections between RTT, interactivity, and QoE. The results indicate that RTT is an insufficient indicator of QoE in productive environments with low RTT values. We outline some precise measures of interactivity needed to capture all the factors that contribute to QoE in remote desktop environments.
Open Access
Online classification of user activities using machine learning on network traffic
(Elsevier, 2020) Labayen Guembe, Víctor; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; Izal Azcárate, Mikel; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
The daily deployment of new applications, along with the exponential increase in network traffic, entails a growth in the complexity of network analysis and monitoring. Conversely, the increasing availability and decreasing cost of computational capacity have increased the popularity and usability of machine learning algorithms. In this paper, a system for classifying user activities from network traffic using both supervised and unsupervised learning is proposed. The system uses the behaviour exhibited over the network and classifies the underlying user activity, taking into consideration all of the traffic generated by the user within a given time window. Those windows are characterised with features extracted from the network and transport layer headers in the traffic flows. A three-layer model is proposed to perform the classification task. The first two layers of the model are implemented using K-Means, while the last one uses a Random Forest to obtain the activity labels. An average accuracy of 97.37% is obtained, with values of precision and recall that allow online classification of network traffic for Quality of Service (QoS) and user profiling, outperforming previous proposals.
Open Access
Traffic generator using Perlin Noise
(IEEE, 2012) Prieto Suárez, Iria; Izal Azcárate, Mikel; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; Automática y Computación; Automatika eta Konputazioa; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Study of high speed networks such as optical next generation burst or packet switched networks require large amounts of synthetic traffic to feed simulators. Methods to generate self-similar long range dependent traffic already exist but they usually work by generating large blocks of traffic of fixed time duration. This limits simulated time or require very high amount of data to be stored before simulation. On this work it is shown how self-similar traffic can be generated using Perlin Noise, an algorithm commonly used to generate 2D/3D noise for natural looking graphics. 1-dimension Perlin Noise can be interpreted as network traffic and used to generate long range dependent traffic for network simulation. The algorithm is compared to more classical approach Random Midpoint Displacement showing at traffic generated is similar but can be generated continuously with no fixed block size.
Open Access
ETOMIC advanced network monitoring system for future Internet experimentation
(Springer-Verlag Berlin Heidelberg, 2010) Csabai, István; Fekete, Attila; Hága, Péter; Hullár, Béla; Kurucz, Gábor; Laki, Sándor; Mátray, Péter; Stéger, József; Vattay, Gábor; Espina Antolín, Félix; García-Jiménez, Santiago; Izal Azcárate, Mikel; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; Aracil Rico, Javier; Gómez, Francisco; González, Iván; López Buedo, Sergio; Moreno, Víctor; Ramos, Javier; Automática y Computación; Automatika eta Konputazioa
ETOMIC is a network traffic measurement platform with high precision GPS-synchronized monitoring nodes. The infrastructure is publicly available to the network research community, supporting advanced experimental techniques by providing high precision hardware equipments and a Central Management System. Researchers can deploy their own active measurement codes to perform experiments on the public Internet. Recently, the functionalities of the original system were significantly extended and new generation measurement nodes were deployed. The system now also includes well structured data repositories to archive and share raw and evaluated data. These features make ETOMIC as one of the experimental facilities that support the design, development and validation of novel experimental techniques for the future Internet. In this paper we focus on the improved capabilities of the management system, the recent extensions of the node architecture and the accompanying database solutions.
Open Access
Computation of traffic time series for large populations of IoT devices
(MDPI, 2018) Izal Azcárate, Mikel; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; García-Jiménez, Santiago; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
En este artículo se estudian las tecnicas para clasificar paquetes de tráfico de red en múltiples clases orientadas a la realización de series temporales de tráfico en escenarios de un elevado numero de clases como pueden ser los proveedores de red para dispositivos IoT. Se muestra que usando técnicas basadas en DStries se pueden monitorizar en tiempo real redes con decenas de miles de dispositivos.
Open Access
Network simulation in a TCP-enabled industrial internet of things environment - reproducibility issues for performance evaluation
(IEEE, 2022) Morató Osés, Daniel; Pérez-Gómara, Carlos; Magaña Lizarrondo, Eduardo; Izal Azcárate, Mikel; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
Network simulation is a tool used to analyse and predict the performance of Industrial Internet of Things deployments while dealing with the complexity of real testbeds. Large network deployments with complex protocols such as Transmission Control Protocol are subject to chaos-theory behaviour, i.e. small changes in the implementation of the protocol stack or simulator behaviour may result in large differences in the performance results. We present the results of simulating two different scenarios using three simulators. The first scenario focuses on the Incast phenomenon in a local area network where sensor data are collected. The second scenario focuses on a congested link traversed by the collected measurements. The performance metrics obtained from the simulators are compared among them and with ground-truth obtained from real network experiments. The results demonstrate how subtle implementation differences in network simulators impact performance results, and how network engineers must consider these differences.
Open Access
Survey on quality of experience evaluation for cloud-based interactive applications
(MDPI, 2024) Arellano Usón, Jesús; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; Izal Azcárate, Mikel; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC
A cloud-based interactive application (CIA) is an application running in the cloud with stringent interactivity requirements, such as remote desktop and cloud gaming. These services have experienced a surge in usage, primarily due to the adoption of new remote work practices during the pandemic and the emergence of entertainment schemes similar to cloud gaming platforms. Evaluating the quality of experience (QoE) in these applications requires specific metrics, including interactivity time, responsiveness, and the assessment of video- and audio-quality degradation. Despite existing studies that evaluate QoE and compare features of general cloud applications, systematic research into QoE for CIAs is lacking. Previous surveys often narrow their focus, overlooking a comprehensive assessment. They touch on QoE in broader contexts but fall short in detailed metric analysis. Some emphasise areas like mobile cloud computing, omitting CIA-specific nuances. This paper offers a comprehensive survey of QoE measurement techniques in CIAs, providing a taxonomy of input metrics, strategies, and evaluation architectures. State-of-the-art proposals are assessed, enabling a comparative analysis of their strengths and weaknesses and identifying future research directions.
Open Access
Midiendo retardos y pérdidas en las redes móviles de alta velocidad
(2015) Prieto Suárez, Iria; Izal Azcárate, Mikel; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; Automática y Computación; Automatika eta Konputazioa
Mobile networks are constantly evolving, but still, due to their nature, it is not trivial to analayse how they face up different kinds of traffic. On the Internet a wide range of services can be found. Usually the majority send large packets, i.e Web services, but others, like VoIP, send small packets. The question is how the mobile networks manage all this traffic. In this work experiments to measure losses and times of sending different packet size bursts are described. Also, preliminary results for experiments with a real network mobile client, are analaysed showing that the performance of the network is different depending on the size of packet.
Open Access
Protocol-agnostic method for monitoring interactivity time in remote desktop services
(Springer Nature, 2021-02-24) Arellano Usón, Jesús; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; Izal Azcárate, Mikel; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC
The growing trend of desktop virtualisation has facilitated the reduction of management costs associated with traditional systems and access to services from devices with different capabilities. However, desktop virtualisation requires controlling the interactivity provided by an infrastructure and the quality of experience perceived by users. This paper proposes a methodology for the quantification of interactivity based on the measurement of the time elapsed between user interactions and the associated responses. Measurement error is controlled using a novel mechanism for the detection of screen changes, which can lead to erroneous measurements. Finally, a campus virtual desktop infrastructure and the Amazon WorkSpaces solution are analysed using this proposed methodology. The results demonstrate the importance of the location of virtualisation infrastructure and the types of protocols used by remote desktop services.