Towards Optimising WLANs Power Saving: Novel Context-aware Network Traffic Classification Based on a Machine Learning Approach

Energy is a vital resource in wireless computing systems. Despite the increasing popularity of Wireless Local Area Networks (WLANs), one of the most important outstanding issues remains the power consumption caused by Wireless Network Interface Controller (WNIC). To save this energy and reduce the overall power consumption of wireless devices, most approaches proposed to-date are focused on static and adaptive power saving modes. Existing literature has highlighted several issues and limitations in regards to their power consumption and performance degradation, warranting the need for further enhancements. In this paper, we propose a novel context-aware network traffic classification approach based on Machine Learning (ML) classifiers for optimizing WLAN power saving. The levels of traffic interaction in the background are contextually exploited for application of ML classifiers. Finally, the classified output traffic is used to optimize our proposed, Context-aware Listen Interval (CALI) power saving modes. A real-world dataset is recorded, based on nine smartphone applications’ network traffic, reflecting different types of network behaviour and interaction. This is used to evaluate the performance of eight ML classifiers in this initial study. Comparative results show that more than 99% of accuracy can be achieved. Our study indicates that ML classifiers are suited for classifying smartphone applications’ network traffic based on levels of interaction in the background

Developing a Systematic Process for Mobile Surveying and Analysis of WLAN security

Wireless Local Area Network (WLAN), familiarly known as Wi-Fi, is one of the most used wireless networking technologies. WLANs have rapidly grown in popularity since the release of the original IEEE 802.11 WLAN standard in 1997. We are using our beloved wireless internet connection for everything and are connecting more and more devices into our wireless networks in every form imaginable. As the number of wireless network devices keeps increasing, so does the importance of wireless network security. During its now over twenty-year life cycle, a multitude of various security measures and protocols have been introduced into WLAN connections to keep our wireless communication secure. The most notable security measures presented in the 802.11 standard have been the encryption protocols Wired Equivalent Privacy (WEP) and Wi-Fi Protected Access (WPA). Both encryption protocols have had their share of flaws and vulnerabilities, some of them so severe that the use of WEP and the first generation of the WPA protocol have been deemed irredeemably broken and unfit to be used for WLAN encryption. Even though the aforementioned encryption protocols have been long since deemed fatally broken and insecure, research shows that both can still be found in use today. The purpose of this Master’s Thesis is to develop a process for surveying wireless local area networks and to survey the current state of WLAN security in Finland. The goal has been to develop a WLAN surveying process that would at the same time be efficient, scalable, and easily replicable. The purpose of the survey is to determine to what extent are the deprecated encryption protocols used in Finland. Furthermore, we want to find out in what state is WLAN security currently in Finland by observing the use of other WLAN security practices. The survey process presented in this work is based on a WLAN scanning method called Wardriving. Despite its intimidating name, wardriving is simply a form of passive wireless network scanning. Passive wireless network scanning is used for collecting information about the surrounding wireless networks by listening to the messages broadcasted by wireless network devices. To collect our research data, we conducted wardriving surveys on three separate occasions between the spring of 2019 and early spring of 2020, in a typical medium-sized Finnish city. Our survey results show that 2.2% out of the located networks used insecure encryption protocols and 9.2% of the located networks did not use any encryption protocol. While the percentage of insecure networks is moderately low, we observed during our study that private consumers are reluctant to change the factory-set default settings of their wireless network devices, possibly exposing them to other security threats

Specification of Smart AP solutions - version 2

This document includes the specification of the second version of the Smart Access Point (AP) Solutions, which are being developed within WP3 of the Wi-5 project. After the Literature Review, a global view of the Wi-5 architecture is presented which includes not only the Smart AP Solutions but also the Cooperative Functionalities being developed in WP4. Next, the Smart AP Solutions are described including the summary of the general approach being followed based on Light Virtual APs (LVAPs). The functionalities enabling Radio Resource Management (i.e. Dynamic Channel Allocation, Load Balancing and Power Control) are reported in detail and the current status of the implementation of the solutions is detailed, with a set of improvements aimed at integrating the support of different channels within the Wi-5 framework. A multi-channel handoff scheme has been designed, requiring a good synchronisation between the different events, in order to make the LVAP switching happen at the same moment when the STA switches its channel. In addition, the beacon generation has been modified in order to improve the scalability and to give a better user experience during handoffs. Tests measuring the handoff delay are presented using three wireless cards from different manufacturers, and using as test traffic a flow of an online game with real-time constraints. The results show that fast handovers ranging from 30 to 200 milliseconds can be achieved. The savings provided by frame aggregation, and its effect on subjective quality have also been studied. A methodology including subjective tests with real users has evaluated this effect, using paired comparison. The results indicate that bandwidth usage savings and especially significant packet rate reduction can be obtained without degrading players’ Quality of Experience (QoE), as long as the overall latency is kept under 100ms. An important finding coming from these results is that the players do not register delay variation introduced by multiplexing

Contributions to IEEE 802.11-based long range communications

The most essential part of the Internet of Things (IoT) infrastructure is the wireless communication system that acts as a bridge for the delivery of data and control messages between the connected things and the Internet. Since the conception of the IoT, a large number of promising applications and technologies have been developed, which will change different aspects in our daily life. However, the existing wireless technologies lack the ability to support a huge amount of data exchange from many battery-driven devices, spread over a wide area. In order to support the IoT paradigm, IEEE 802.11ah is an Internet of Things enabling technology, where the efficient management of thousands of devices is a key function. This is one of the most promising and appealing standards, which aims to bridge the gap between traditional mobile networks and the demands of the IoT. To this aim, IEEE 802.11ah provides the Restricted Access Window (RAW) mechanism, which reduces contention by enabling transmissions for small groups of stations. Optimal grouping of RAW stations requires an evaluation of many possible configurations. In this thesis, we first discuss the main PHY and MAC layer amendments proposed for IEEE 802.11ah. Furthermore, we investigate the operability of IEEE 802.11ah as a backhaul link to connect devices over possibly long distances. Additionally, we compare the aforementioned standard with previous notable IEEE 802.11 amendments (i.e. IEEE 802.11n and IEEE 802.11ac) in terms of throughput (with and without frame aggregation) by utilizing the most robust modulation schemes. The results show an improved performance of IEEE 802.11ah (in terms of power received at long range while experiencing different packet error rates) as compared to previous IEEE 802.11 standards. Additionally, we expose the capabilities of future IEEE 802.11ah in supporting different IoT applications. In addition, we provide a brief overview of the technology contenders that are competing to cover the IoT communications framework. Numerical results are presented showing how the future IEEE 802.11ah specification offers the features required by IoT communications, thus putting forward IEEE 802.11ah as a technology to cater the needs of the Internet of Things paradigm. Finally, we propose an analytical model (named e-model) that provides an evaluation of the RAW onfiguration performance, allowing a fast adaptation of RAW grouping policies, in accordance to varying channel conditions. We base the e-model in known saturation models, which we adapted to include the IEEE 802.11ah’s PHY and MAC layer modifications and to support different bit rate and packet sizes. As a proof of concept, we use the proposed model to compare the performance of different grouping strategies,showing that the e-model is a useful analysis tool in RAW-enabled scenarios. We validate the model with existing IEEE 802.11ah implementation for ns-3.La clave del concepto Internet de las cosas (IoT) es que utiliza un sistema de comunicación inalámbrica, el cual actúa como puente para la entrega de datos y mensajes de control entre las "cosas" conectadas y el Internet. Desde la concepción del IoT, se han desarrollado gran cantidad de aplicaciones y tecnologías prometedoras que cambiarán distintos aspectos de nuestra vida diaria.Sin embargo, las tecnologías de redes computacionales inalámbricas existentes carecen de la capacidad de soportar las características del IoT, como las grandes cantidades de envío y recepción de datos desde múltiples dispositivos distribuidos en un área amplia, donde los dispositivos IoT funcionan con baterías. Para respaldar el paradigma del IoT, IEEE 802.11ah, la cual es una tecnología habilitadora del Internet de las cosas, para el cual la gestión eficiente de miles de dispositivos es una función clave. IEEE 802.11ah es uno de los estándares más prometedores y atractivos, desde su concepción orientada para IoT, su objetivo principal es cerrar la brecha entre las redes móviles tradicionales y la demandada por el IoT. Con este objetivo en mente, IEEE 802.11ah incluye entre sus características especificas el mecanismo de ventana de acceso restringido (RAW, por sus siglas en ingles), el cual define un nuevo período de acceso al canal libre de contención, reduciendo la misma al permitir transmisiones para pequeños grupos de estaciones. Nótese que para obtener una agrupación óptima de estaciones RAW, se requiere una evaluación de las distintas configuraciones posibles. En esta tesis, primero discutimos las principales mejoras de las capas PHY y MAC propuestas para IEEE 802.11ah. Además, investigamos la operatividad de IEEE 802.11ah como enlace de backhaul para conectar dispositivos a distancias largas. También, comparamos el estándar antes mencionado con las notables especificaciones IEEE 802.11 anteriores (es decir, IEEE 802.11n y IEEE 802.11ac), en términos de rendimiento (incluyendo y excluyendo la agregación de tramas de datos) y utilizando los esquemas de modulación más robustos. Los resultados muestran mejores resultados en cuanto al rendimiento de IEEE 802.11ah (en términos de potencia recibida a largo alcance, mientras se experimentan diferentes tasas de error de paquetes de datos) en comparación con los estándares IEEE 802.11 anteriores.Además, exponemos las capacidades de IEEE 802.11ah para admitir diferentes aplicaciones de IoT. A su vez, proporcionamos una descripción general de los competidores tecnológicos, los cuales contienden para cubrir el marco de comunicaciones IoT. También se presentan resultados numéricos que muestran cómo la especificación IEEE 802.11ah ofrece las características requeridas por las comunicaciones IoT, presentando así a IEEE 802.11ah como una tecnología que puede satisfacer las necesidades del paradigma de Internet de las cosas.Finalmente, proponemos un modelo analítico (denominado e-model) que proporciona una evaluación del rendimiento utilizando la característica RAW con múltiples configuraciones, el cual permite una rápida adaptación de las políticas de agrupación RAW, de acuerdo con las diferentes condiciones del canal de comunicación. Basamos el e-model en modelos de saturación conocidos, que adaptamos para incluir las modificaciones de la capa MAC y PHY de IEEE 802.11ah y para poder admitir diferentes velocidades de transmisión de datos y tamaños de paquetes. Como prueba de concepto, utilizamos el modelo propuesto para comparar el desempeño de diferentes estrategias de agrupación, mostrando que el e-model es una herramienta de análisis útil en escenarios habilitados para RAW. Cabe mencionar que también validamos el modelo con la implementación IEEE 802.11ah existente para ns-3

Doctor of Philosophy

dissertationThe continuous growth of wireless communication use has largely exhausted the limited spectrum available. Methods to improve spectral efficiency are in high demand and will continue to be for the foreseeable future. Several technologies have the potential to make large improvements to spectral efficiency and the total capacity of networks including massive multiple-input multiple-output (MIMO), cognitive radio, and spatial-multiplexing MIMO. Of these, spatial-multiplexing MIMO has the largest near-term potential as it has already been adopted in the WiFi, WiMAX, and LTE standards. Although transmitting independent MIMO streams is cheap and easy, with a mere linear increase in cost with streams, receiving MIMO is difficult since the optimal methods have exponentially increasing cost and power consumption. Suboptimal MIMO detectors such as K-Best have a drastically reduced complexity compared to optimal methods but still have an undesirable exponentially increasing cost with data-rate. The Markov Chain Monte Carlo (MCMC) detector has been proposed as a near-optimal method with polynomial cost, but it has a history of unusual performance issues which have hindered its adoption. In this dissertation, we introduce a revised derivation of the bitwise MCMC MIMO detector. The new approach resolves the previously reported high SNR stalling problem of MCMC without the need for hybridization with another detector method or adding heuristic temperature scaling terms. Another common problem with MCMC algorithms is an unknown convergence time making predictable fixed-length implementations problematic. When an insufficient number of iterations is used on a slowly converging example, the output LLRs can be unstable and overconfident, therefore, we develop a method to identify rare, slowly converging runs and mitigate their degrading effects on the soft-output information. This improves forward-error-correcting code performance and removes a symptomatic error floor in bit-error-rates. Next, pseudo-convergence is identified with a novel way to visualize the internal behavior of the Gibbs sampler. An effective and efficient pseudo-convergence detection and escape strategy is suggested. Finally, the new excited MCMC (X-MCMC) detector is shown to have near maximum-a-posteriori (MAP) performance even with challenging, realistic, highly-correlated channels at the maximum MIMO sizes and modulation rates supported by the 802.11ac WiFi specification, 8x8 256 QAM. Further, the new excited MCMC (X-MCMC) detector is demonstrated on an 8-antenna MIMO testbed with the 802.11ac WiFi protocol, confirming its high performance. Finally, a VLSI implementation of the X-MCMC detector is presented which retains the near-optimal performance of the floating-point algorithm while having one of the lowest complexities found in the near-optimal MIMO detector literature

Wireless mesh networks for smart-grids

Tese de mestrado. Mestrado Integrado em Engenharia Electrotécnica e de Computadores - Major Telecomunicações. Faculdade de Engenharia. Universidade do Porto. 201

Shape detection of physical objects with Intel 5300 and the 802.11n CSI Tool

This thesis presents a detailed look at channel state information (CSI), an efficient approach to the shape detection of physical objects, and observations on how environment noise affects CSI. CSI describes the communication link between a transmitter and receiver through the properties of multiple channels. Once analyzed, these channels or subcarriers describe how the signal travels from the transmitting device to the receiving device. While this information was intended to help increase signal quality and strength of a communication link, many other applications have been suggested. The proposed application in this paper provides a way with minimal resources to capture and utilize CSI for shape detection. Instead of relying on gestures or movements, I focus on the experiment setup used to detect object shapes and their respective CSI signature. Hence, if I can determine the shape an object should be, then I can detect when that shape changes and capture specific events. In addition, I utilize Wi-Fi as a common source available to provide CSI in many real-world applications without the need for additional resources. Experimentally, I demonstrate how to build a system capable of capturing CSI, how to use CSI logging tools, how environment noise affects CSI, and an approach to detect shape changes