Situation-aware Edge Computing

Future wireless networks must cope with an increasing amount of data that needs to be transmitted to or from mobile devices. Furthermore, novel applications, e.g., augmented reality games or autonomous driving, require low latency and high bandwidth at the same time. To address these challenges, the paradigm of edge computing has been proposed. It brings computing closer to the users and takes advantage of the capabilities of telecommunication infrastructures, e.g., cellular base stations or wireless access points, but also of end user devices such as smartphones, wearables, and embedded systems. However, edge computing introduces its own challenges, e.g., economic and business-related questions or device mobility. Being aware of the current situation, i.e., the domain-specific interpretation of environmental information, makes it possible to develop approaches targeting these challenges. In this thesis, the novel concept of situation-aware edge computing is presented. It is divided into three areas: situation-aware infrastructure edge computing, situation-aware device edge computing, and situation-aware embedded edge computing. Therefore, the concepts of situation and situation-awareness are introduced. Furthermore, challenges are identified for each area, and corresponding solutions are presented. In the area of situation-aware infrastructure edge computing, economic and business-related challenges are addressed, since companies offering services and infrastructure edge computing facilities have to find agreements regarding the prices for allowing others to use them. In the area of situation-aware device edge computing, the main challenge is to find suitable nodes that can execute a service and to predict a node’s connection in the near future. Finally, to enable situation-aware embedded edge computing, two novel programming and data analysis approaches are presented that allow programmers to develop situation-aware applications. To show the feasibility, applicability, and importance of situation-aware edge computing, two case studies are presented. The first case study shows how situation-aware edge computing can provide services for emergency response applications, while the second case study presents an approach where network transitions can be implemented in a situation-aware manner

Immersive interconnected virtual and augmented reality : a 5G and IoT perspective

Despite remarkable advances, current augmented and virtual reality (AR/VR) applications are a largely individual and local experience. Interconnected AR/VR, where participants can virtually interact across vast distances, remains a distant dream. The great barrier that stands between current technology and such applications is the stringent end-to-end latency requirement, which should not exceed 20 ms in order to avoid motion sickness and other discomforts. Bringing AR/VR to the next level to enable immersive interconnected AR/VR will require significant advances towards 5G ultra-reliable low-latency communication (URLLC) and a Tactile Internet of Things (IoT). In this article, we articulate the technical challenges to enable a future AR/VR end-to-end architecture, that combines 5G URLLC and Tactile IoT technology to support this next generation of interconnected AR/VR applications. Through the use of IoT sensors and actuators, AR/VR applications will be aware of the environmental and user context, supporting human-centric adaptations of the application logic, and lifelike interactions with the virtual environment. We present potential use cases and the required technological building blocks. For each of them, we delve into the current state of the art and challenges that need to be addressed before the dream of remote AR/VR interaction can become reality

Towards Viable Large Scale Heterogeneous Wireless Networks

We explore radio resource allocation and management issues related to a large-scale heterogeneous (hetnet) wireless system made up of several Radio Access Technologies (RATs) that collectively provide a unified wireless network to a diverse set of users through co-ordination managed by a centralized Global Resource Controller (GRC). We incorporate 3G cellular technologies HSPA and EVDO, 4G cellular technologies WiMAX and LTE, and WLAN technology Wi-Fi as the RATs in our hetnet wireless system. We assume that the user devices are either multi-modal or have one or more reconfigurable radios which makes it possible for each device to use any available RAT at any given time subject to resource-sharing agreements. For such a hetnet system where resource allocation is coordinated at a global level, characterizing the network performance in terms of various conflicting network efficiency objectives that takes costs associated with a network re-association operation into account largely remains an open problem. Also, all the studies to-date that try to characterize the network performance of a hetnet system do not account for RAT-specific implementation details and the management overhead associated with setting up a centralized control. We study the radio resource allocation problem and the implementation/management overhead issues associated with a hetnet system in two research phases. In the first phase, we develop cost models associated with network re-association in terms of increased power consumption and communication downtime taking into account various user device assumptions. Using these cost models in our problem formulations, the first phase focuses on resource allocation strategies where we use a high-level system modeling approach to study the achievable performance in terms of conflicting network efficiency measures of spectral efficiency, overall power consumption, and instantaneous and long-term fairness for each user in the hetnet system. Our main result from this phase of study suggests that the gain in spectral efficiency due to multi-access network diversity results in a tremendous increase in overall power consumption due to frequent re-associations required by user devices. We then develop a utility function-based optimization algorithm to characterize and achieve a desired tradeoff in terms of all four network efficiency measures of spectral efficiency, overall power consumption and instantaneous and long-term fairness. We show an increase in a multi-attribute system utility measure of up to 56.7% for our algorithm compared to other widely studied resource allocation algorithms including max-sum rate, proportional fairness, max-min fairness and min power. The second phase of our research study focuses on practical implementation issues including the overhead required to implement a centralized GRC solution in a hetnet system. Through detailed protocol level simulations performed in ns-2, we show an increase in spectral efficiency of up to 99% and an increase in instantaneous fairness of up to 28.5% for two sort-based user device-to-Access Point (AP)/Base Station (BS) association algorithms implemented at the GRC that aim to maximize system spectral efficiency and instantaneous fairness performance metrics respectively compared to a distributed solution where each user makes his/her own association decision. The efficiency increase for each respective attribute again results in a tremendous increase in power consumption of up to 650% and 794% for each respective algorithm implemented at the GRC compared to a distributed solution because of frequent re-associations

A survey on mobility-induced service migration in the fog, edge, and related computing paradigms

The final publication is available at ACM via http://dx.doi.org/10.1145/3326540With the advent of fog and edge computing paradigms, computation capabilities have been moved toward the edge of the network to support the requirements of highly demanding services. To ensure that the quality of such services is still met in the event of users’ mobility, migrating services across different computing nodes becomes essential. Several studies have emerged recently to address service migration in different edge-centric research areas, including fog computing, multi-access edge computing (MEC), cloudlets, and vehicular clouds. Since existing surveys in this area focus on either VM migration in general or migration in a single research field (e.g., MEC), the objective of this survey is to bring together studies from different, yet related, edge-centric research fields while capturing the different facets they addressed. More specifically, we examine the diversity characterizing the landscape of migration scenarios at the edge, present an objective-driven taxonomy of the literature, and highlight contributions that rather focused on architectural design and implementation. Finally, we identify a list of gaps and research opportunities based on the observation of the current state of the literature. One such opportunity lies in joining efforts from both networking and computing research communities to facilitate future research in this area.Peer ReviewedPreprin

Investigating seamless handover in VANET systems

Wireless communications have been extensively studied for several decades, which has led to various new advancements, including new technologies in the field of Intelligent Transport Systems. Vehicular Ad hoc Networks or VANETs are considered to be a long-term solution, contributing significantly towards Intelligent Transport Systems in providing access to critical life-safety applications and infotainment services. These services will require ubiquitous connectivity and hence there is a need to explore seamless handover mechanisms. Although VANETs are attracting greater commercial interest, current research has not adequately captured the realworld constraints in Vehicular Ad hoc Network handover techniques. Due to the high velocity of the vehicles and smaller coverage distances, there are serious challenges in providing seamless handover from one Road Side Unit (RSU) to another and this comes at the cost of overlapping signals of adjacent RSUs. Therefore, a framework is needed to be able to calculate the regions of overlap in adjacent RSU coverage ranges to guarantee ubiquitous connectivity. This thesis is about providing such a framework by analysing in detail the communication mechanisms in a VANET network, firstly by means of simulations using the VEINs framework via OMNeT++ and then using analytical analysis of the probability of successful packet reception. Some of the concepts of the Y-Comm architecture such as Network Dwell Time, Time Before Handover and Exit Times have been used to provide a framework to investigate handover issues and these parameters are also used in this thesis to explore handover in highly mobile environments such as VANETs. Initial investigation showed that seamless communication was dependant on the beacon frequency, length of the beacon and the velocity of the vehicle. The effects of each of these parameters are explored in detail and results are presented which show the need for a more probabilistic approach to handover based on cumulative probability of successful packet reception. In addition, this work shows how the length of the beacon affects the rate of change of the Signal-to-Noise ratio or SNR as the vehicle approaches the Road-Side Unit. However, the velocity of the vehicle affects both the cumulative probability as well as the Signal-to-Noise ratio as the vehicle approaches the Road-Side Unit. The results of this work will enable systems that can provide ubiquitous connectivity via seamless handover using proactive techniques because traditional models of handover are unable to cope with the high velocity of the vehicles and relatively small area of coverage in these environments. Finally, a testbed has been set-up at the Middlesex University, Hendon campus for the purpose of achieving a better understanding of VANET systems operating in an urban environment. Using the testbed, it was observed that environmental effects have to be taken into considerations in real-time deployment studies to see how these parameters can affect the performance of VANET systems under different scenarios. This work also highlights the fact that in order to build a practical system better propagation models are required in the urban context for highly mobile environments such as VANETs

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

Support of resource-aware vertical handovers in WLAN hotspots

Endgeräte wie Smartphones oder Tablets bieten häufig eine Vielfalt drahtloser Zugänge zum Internet an. Üblicherweise schließt dies die 802.11 WLANs und auch Technologien drahtloser Weitverkehrsnetze (WWANs) aus dem Bereich LTE oder WiMAX ein. Aufgrund dieser Optionen haben sich die Endanwender daran gewöhnt, überall und zu jeder Zeit auf ihre Internetdienste zuzugreifen. Damit hat auch der Datenverkehr pro Anwender zugenommen, was eine Herausforderung insbesondere für die Betreiber von WWANs ist. Soweit verfügbar, favorisieren Endanwender heutzutage eher einen drahtlosen Zugang zum Internet über WLANs als über WWANs. Des Weiteren haben die 3GPP-Standardisierungsgremien Ansätze erarbeitet, die zusätzlich Verkehr aus WWANs in Netze mit geringerer Abdeckung wie WLAN- oder Femto-Zellen abgeben. Solche Ansätze werden auch als "Traffic Offloading" bezeichnet und haben das Ziel, die WWANs zu entlasten. Dabei werden jedoch eher einfache Strategien verfolgt, die auf der Nutzung zusätzlicher Kapazitäten heterogener Netze beruhen und dann angewendet werden, wenn ein alternatives Zugangsnetz für ein Endgerät verfügbar ist. Im Rahmen dieser Arbeit zeigen wir Gewinne auf, die entstehen, wenn man die Auswahl der Endgeräte für ein WLAN-Netz stattdessen auf Basis der von ihnen belegten Ressourcen durchführt. In diesem Kontext schlagen wir vor, Geräte mit stark negativem Einfluss auf die WLAN-Kapazität wieder zurück in das WWAN zu reichen, was wir als "Onloading" bezeichnen. Ein solches "Onloading" zieht Herausforderungen in unterschiedlichen Richtungen mit sich. Die fortschreitende Miniaturisierung hat in den letzten Jahren zu dem Trend geführt, die Anzahl der Netzwerkkarten (NICs) in Endgeräten zu reduzieren. Wir bezeichnen eine NIC als multimodal, wenn sie mehrere Funktechnologien unterstützt, aber zu einem bestimmten Zeitpunkt immer nur eine davon genutzt werden kann. Deswegen stellt für eine multimodale NIC das "Onloading" während einer laufenden Verbindung eine Herausforderung dar. Wir schlagen einen Ansatz vor, der vorbereitende Mechanismen für ein "Onloading" als auch eine laufende Verbindung im WLAN über eine solche NIC ermöglicht. Des Weiteren ist es wichtig, in einem WLAN Hotspot zu entscheiden, welche Geräte einen negativen Einfluss auf die Kapazität des Netzes haben. Dafür haben wir eine Metrik entwickelt, die eine Entscheidungsgrundlage für das Onloading bildet. Diese Metrik basiert rein auf einer Beobachtung des Netzes und seiner Geräte, ermöglicht jedoch keine Entscheidung für sich neu assoziierende Geräte im WLAN. Erschwerend kommt hinzu, dass viele Eigenschaften der NICs durch herstellerabhängige Implementierungen geprägt werden. Solche Algorithmen bieten eine zusätzliche Herausforderung, da ihre internen Abläufe üblicherweise unbekannt sind. Ein bekanntes Beispiel für solche Algorithmen stellt die Anpassung der WLAN-Link-Datenraten dar. Diese Algorithmen wählen die jeweiligen Modulations- und Kodierungsschemata (MCSs) für die drahtlosen Übertragungen aus. Robuste MCSs resultieren dabei in geringere Link-Datenraten und haben somit einen starken Einfluss auf die Kapazität einer WLAN-Zelle. Aus diesem Grund fokussieren wir uns auf eine Abschätzung der Datenratenwahl eines Endgerätes. Damit lassen sich im Vorfeld Aussagen treffen, ob ein Gerät starken Einfluss auf die WLAN-Kapazität haben wird, so dass es für ein "Onloading" in Frage kommt.End-user devices such as smart phones and tablets have become very popular as they offer a variety of wireless Internet accesses ranging from the WLAN standards to WWAN technologies such as LTE or even WiMAX. Due to these different wireless access options and new emerging applications—e.g., from the areas of video streaming, social networks, as well as Internet clouds—people are increasingly connecting to the Internet with their de- vices while being on the move. In line with this, the number of devices as well as the traffic demand of end users have been reported to increase rapidly over the last years which imposes a strong challenge especially for the operators of WWANs. Thereby, end users frequently tend to use settings that favor a connectivity to the Internet whenever possible rather over WLAN than over WWAN access. Further, the cellular standardization bodies of the 3GPP envision solutions to hand over on-going wireless sessions from cellular to other small cell accesses such as WLANs or femto cells. This is also known as traffic offloading essentially freeing capacity in terms of users with a certain service in the cellular accesses. Nevertheless this offloading follows a rather simple strategy to utilize additional capacity of heterogeneous accesses such as WLANs whenever being available for a given device. This thesis shows that stronger gains can be expected if the selection of devices to be served in WLANs is conducted in a resource-aware fashion including an evaluation of the WLAN traffic in terms of the channel occupation time and MAC overhead as result of contention, interference, and fluctuating channels. In this context, this thesis envisions to onload unfavorable devices negatively affecting the WLAN capacity back to WWAN accesses. A support of such an onloading imposes challenges in different dimensions. From the hardware design of devices, there is a strong trend to limit the number of separate network interface cards (NICs) due to space and cost issues. We refer to a multi-mode NIC if it covers multiple technologies, while at a given time only access to one technology is possible. Thus, smoothly onloading a device with such a NIC is by far not trivial. We present an approach that conducts handover preparation mechanisms, while also allowing a continuous WLAN communication over a multi-mode NIC. Further, it is by far not trivial to judge which subset of associated devices is negatively affecting the capacity of a WLAN hotspot. Thus, a careful evaluation of devices regarding a selection for an onloading back to WWAN accesses imposes a challenge yet. In this direction, we present a performance metric that identifies devices degrading the WLAN capacity. While our performance metric tackles a reactive selection, it falls short to support a predictive evaluation, e.g., of devices which just joined the WLAN cell. Even worse, proprietary algorithms inside a WLAN stack impose a severe challenge as their internal routines are usually not conveyed via typical management interfaces. A well-known example for this category of algorithms are the link data rate adaptation schemes, with which WLAN devices adjust the modulation and coding scheme (MCS) for their transmissions. As MCSs resulting in low link data rates may specifically degrade the capacity of a WLAN cell, we focus on an estimation regarding the data rate selection of a device as a third contribution of this thesis. This estimation enables to select devices that will likely degrade the capacity of the WLAN hotspot for an onloading in advance

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

Exploiting user contention to optimize proactive resource allocation in future networks

In order to provide ubiquitous communication, seamless connectivity is now required in all environments including highly mobile networks. By using vertical handover techniques it is possible to provide uninterrupted communication as connections are dynamically switched between wireless networks as users move around. However, in a highly mobile environment, traditional reactive approaches to handover are inadequate. Therefore, proactive handover techniques, in which mobile nodes attempt to determine the best time and place to handover to local networks, are actively being investigated in the context of next generation mobile networks. The Y-Comm Framework which looks at proactive handover techniques has de�fined two key parameters: Time Before Handover and the Network Dwell Time, for any given network topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is now possible to express contention for resources in terms of: No Contention, Partial Contention and Full Contention. As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. In this thesis, the contention for channel resources being allocated to mobile nodes is analysed. The work presents a new methodology to support proactive resource allocation for emerging future networks such as Vehicular Ad-Hoc Networks (VANETs) by allowing us to calculate the probability of contention based on user demand of network resources. These results are veri�ed using simulation. In addition, this proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This thesis also presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments. The results show that the analysis of user contention does provide a proactive mechanism to improve the performance of resource allocation in mobile networks

Towards edge robotics: the progress from cloud-based robotic systems to intelligent and context-aware robotic services

Current robotic systems handle a different range of applications such as video surveillance, delivery of goods, cleaning, material handling, assembly, painting, or pick and place services. These systems have been embraced not only by the general population but also by the vertical industries to help them in performing daily activities. Traditionally, the robotic systems have been deployed in standalone robots that were exclusively dedicated to performing a specific task such as cleaning the floor in indoor environments. In recent years, cloud providers started to offer their infrastructures to robotic systems for offloading some of the robot’s functions. This ultimate form of the distributed robotic system was first introduced 10 years ago as cloud robotics and nowadays a lot of robotic solutions are appearing in this form. As a result, standalone robots became software-enhanced objects with increased reconfigurability as well as decreased complexity and cost. Moreover, by offloading the heavy processing from the robot to the cloud, it is easier to share services and information from various robots or agents to achieve better cooperation and coordination. Cloud robotics is suitable for human-scale responsive and delay-tolerant robotic functionalities (e.g., monitoring, predictive maintenance). However, there is a whole set of real-time robotic applications (e.g., remote control, motion planning, autonomous navigation) that can not be executed with cloud robotics solutions, mainly because cloud facilities traditionally reside far away from the robots. While the cloud providers can ensure certain performance in their infrastructure, very little can be ensured in the network between the robots and the cloud, especially in the last hop where wireless radio access networks are involved. Over the last years advances in edge computing, fog computing, 5G NR, network slicing, Network Function Virtualization (NFV), and network orchestration are stimulating the interest of the industrial sector to satisfy the stringent and real-time requirements of their applications. Robotic systems are a key piece in the industrial digital transformation and their benefits are very well studied in the literature. However, designing and implementing a robotic system that integrates all the emerging technologies and meets the connectivity requirements (e.g., latency, reliability) is an ambitious task. This thesis studies the integration of modern Information andCommunication Technologies (ICTs) in robotic systems and proposes some robotic enhancements that tackle the real-time constraints of robotic services. To evaluate the performance of the proposed enhancements, this thesis departs from the design and prototype implementation of an edge native robotic system that embodies the concepts of edge computing, fog computing, orchestration, and virtualization. The proposed edge robotics system serves to represent two exemplary robotic applications. In particular, autonomous navigation of mobile robots and remote-control of robot manipulator where the end-to-end robotic system is distributed between the robots and the edge server. The open-source prototype implementation of the designed edge native robotic system resulted in the creation of two real-world testbeds that are used in this thesis as a baseline scenario for the evaluation of new innovative solutions in robotic systems. After detailing the design and prototype implementation of the end-to-end edge native robotic system, this thesis proposes several enhancements that can be offered to robotic systems by adapting the concept of edge computing via the Multi-Access Edge Computing (MEC) framework. First, it proposes exemplary network context-aware enhancements in which the real-time information about robot connectivity and location can be used to dynamically adapt the end-to-end system behavior to the actual status of the communication (e.g., radio channel). Three different exemplary context-aware enhancements are proposed that aim to optimize the end-to-end edge native robotic system. Later, the thesis studies the capability of the edge native robotic system to offer potential savings by means of computation offloading for robot manipulators in different deployment configurations. Further, the impact of different wireless channels (e.g., 5G, 4G andWi-Fi) to support the data exchange between a robot manipulator and its remote controller are assessed. In the following part of the thesis, the focus is set on how orchestration solutions can support mobile robot systems to make high quality decisions. The application of OKpi as an orchestration algorithm and DLT-based federation are studied to meet the KPIs that autonomously controlledmobile robots have in order to provide uninterrupted connectivity over the radio access network. The elaborated solutions present high compatibility with the designed edge robotics system where the robot driving range is extended without any interruption of the end-to-end edge robotics service. While the DLT-based federation extends the robot driving range by deploying access point extension on top of external domain infrastructure, OKpi selects the most suitable access point and computing resource in the cloud-to-thing continuum in order to fulfill the latency requirements of autonomously controlled mobile robots. To conclude the thesis the focus is set on how robotic systems can improve their performance by leveraging Artificial Intelligence (AI) and Machine Learning (ML) algorithms to generate smart decisions. To do so, the edge native robotic system is presented as a true embodiment of a Cyber-Physical System (CPS) in Industry 4.0, showing the mission of AI in such concept. It presents the key enabling technologies of the edge robotic system such as edge, fog, and 5G, where the physical processes are integrated with computing and network domains. The role of AI in each technology domain is identified by analyzing a set of AI agents at the application and infrastructure level. In the last part of the thesis, the movement prediction is selected to study the feasibility of applying a forecast-based recovery mechanism for real-time remote control of robotic manipulators (FoReCo) that uses ML to infer lost commands caused by interference in the wireless channel. The obtained results are showcasing the its potential in simulation and real-world experimentation.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Karl Holger.- Secretario: Joerg Widmer.- Vocal: Claudio Cicconett