Das Hauptproblem von Lokalisierungsalgorithmen für WSNs basierend auf Ankerknoten ist die Abhängigkeit von diesen. Mobilität im Netzwerk kann zu Topologien führen, in denen einzelne Knoten oder ganze Teile des Netzwerks temporär von allen Ankerknoten isoliert werden. In diesen Fällen ist keine weitere Lokalisierung möglich. Dies wirkt sich primär auf den Lokalisierungsfehler aus, der in diesen Fällen stark ansteigt. Des weiteren haben Betreiber von Sensornetzwerken Interesse daran, die Anzahl der kosten- und wartungsintensiveren Ankerknoten auf ein Minimum zu reduzieren. Dies verstärkt zusätzlich das Problem von nicht verfügbaren Ankerknoten während des Netzwerkbetriebs. In dieser Arbeit werden zunächst die Vor- und Nachteile der beiden großen Hauptkategorien von Lokalisierungsalgorithmen (range-based und range-free Verfahren) diskutiert und eine Studie eines oft für range-based Lokalisierung genutzten Distanzbestimmungsverfahren mit Hilfe des RSSI vorgestellt. Danach werden zwei neue Varianten für ein bekanntes range-free Lokalisierungsverfahren mit Namen MCL eingeführt. Beide haben zum Ziel das Problem der temporär nicht verfügbaren Ankerknoten zu lösen, bedienen sich dabei aber unterschiedlicher Mittel. SA-MCL nutzt ein dead reckoning Verfahren, um die Positionsschätzung vom letzten bekannten Standort weiter zu führen. Dies geschieht mit Hilfe von zusätzlichen Sensorinformationen, die von einem elektronischen Kompass und einem Beschleunigungsmesser zur Verfügung gestellt werden. PO-MCL hingegen nutzt das Mobilitätsverhalten von einigen Anwendungen in Sensornetzwerken aus, bei denen sich alle Knoten primär auf einer festen Anzahl von Pfaden bewegen, um den Lokalisierungsprozess zu verbessern. Beide Methoden werden durch detaillierte Netzwerksimulationen evaluiert. Im Fall von SA-MCL wird außerdem eine Implementierung auf echter Hardware vorgestellt und eine Feldstudie in einem mobilen Sensornetzwerk durchgeführt. Aus den Ergebnissen ist zu sehen, dass der Lokalisierungsfehler in Situationen mit niedriger Ankerknotendichte im Fall von SA-MCL um bis zu 60% reduziert werden kann, beziehungsweise um bis zu 50% im Fall von PO-MCL.

In the context of telecommunication networks, the user attribution problem refers to the challenge faced in recognizing communication traffic as belonging to a given user when information needed to identify the user is missing. This is analogous to trying to recognize a nameless face in a crowd. This problem worsens as users move across many mobile networks (complex networks) owned and operated by different providers. The traditional approach of using the source IP address, which indicates where a packet comes from, does not work when used to identify mobile users. Recent efforts to address this problem by exclusively relying on web browsing behavior to identify users were limited to a small number of users (28 and 100 users). This was due to the inability of solutions to link up multiple user sessions together when they rely exclusively on the web sites visited by the user. This study has tackled this problem by utilizing behavior based identification while accounting for time and the sequential order of web visits by a user. Hierarchical Temporal Memories (HTM) were used to classify historical navigational patterns for different users. Each layer of an HTM contains variable order Markov chains of connected nodes which represent clusters of web sites visited in time order by the user (user sessions). HTM layers enable inference "generalization" by linking Markov chains within and across layers and thus allow matching longer sequences of visited web sites (multiple user sessions). This approach enables linking multiple user sessions together without the need for a tracking identifier such as the source IP address. Results are promising. HTMs can provide high levels of accuracy using synthetic data with 99% recall accuracy for up to 500 users and good levels of recall accuracy of 95 % and 87% for 5 and 10 users respectively when using cellular network data. This research confirmed that the presence of long tail web sites (rarely visited) among many repeated destinations can create unique differentiation. What was not anticipated prior to this research was the very high degree of repetitiveness of some web destinations found in real network data.

The demand of mobile users with high data-rate services continues to increase. To satisfy the needs of such mobile users, operators must continue to enhance their existing networks. The radio interface is a well-known bottleneck because the radio spectrum is limited and therefore expensive. Efficient use of the radio spectrum is, therefore, very important. To utilise the spectrum efficiently, any of the channels can be used simultaneously in any of the cells as long as interference generated by the base stations using the same channels is below an acceptable level. In cellular networks based on Orthogonal Frequency Division Multiple Access (OFDMA), inter-cell interference reduces the performance of the link throughput to users close to the cell edge. To improve the performance of cell-edge users, a technique called Coordinated Multi-Point (CoMP) transmission is being researched for use in the next generation of cellular networks. For a network to benefit from CoMP, its utilisation of resources should be scheduled efficiently. The thesis focuses on the resource scheduling algorithm development for CoMP joint transmission scheme in OFDMA-based cellular networks. In addition to the algorithm, the thesis provides an analytical framework for the performance evaluation of the CoMP technique. From the system level simulation results, it has been shown that the proposed resource scheduling based on a joint maximum throughput provides higher spectral efficiency compared with a joint proportional fairness scheduling algorithm under different traffic loads in the network and under different criteria of making cell-edge decision. A hybrid model combining the analytical and simulation approaches has been developed to evaluate the average system throughput. It has been found that the results of the hybrid model are in line with the simulation based results. The benefit of the model is that the throughput of any possible call state in the system can be evaluated. Two empirical path loss models in an indoor-to-outdoor environment of a residential area have been developed based on the measurement data at carrier frequencies 900 MHz and 2 GHz. The models can be used as analytical expressions to estimate the level of interference by a femtocell to a macrocell user in link-level simulations.

Mobile edge computing (MEC) has been considered as a promising technology to handle computation-intensive and latency-sensitive tasks for mobile user equipments (UEs) in next-generation mobile networks. Mobile UEs can offload these tasks to nearby edge servers, which are typically deployed on base stations (BSs) that are equipped with computation resources. Thus, the task execution latency as well as the energy consumption of mobile devices can be reduced. Mobility management has played a fundamental role in MEC, which associates UEs with the appropriate BSs. In the existing handover decision-making process, the communication costs dominate. However, in edge scenario, the computation capacity constraints should also be considered. Due to user mobility, mobile UEs are nonuniformly distributed over time and space. Edge servers in hot-spot areas can be overloaded while others are underloaded. When edge servers are densely deployed, each UE may have multiple choices to offload its tasks. Instead, if edge servers are sparsely deployed, UEs may only have one option for task offloading. This aggravates the unbalanced workload of the deployed edge servers. Therefore, how to serve the dynamic hot-spot areas needs to be addressed in different edge server deployment scenarios. Considering these two scenarios discussed above, two problems are addressed in this thesis: 1) with densely deployed edge servers, for each mobile UE, how to choose the appropriate edge servers independently without full system information is inves- tigated, and 2) with sparsely deployed edge servers, how to serve dynamic hot-spot areas in an efficient and flexible way is emphasized. First, with BSs densely de- ployed in hot-spot areas, mobile UEs can offload their tasks to one of the available edge servers nearby. However, precise full system information such as the server workload can be hard to be synchronized in real time, which also introduces extra signaling overhead for mobility management decision-making. Thus, a user-centric reinforcement-learning-based mobility management scheme is proposed to handle sys- tem uncertainties. Each UE observes the task latency and automatically learns the optimal mobility management strategy through trial and feedback. Simulation results show that the proposed scheme manifests superiority in dealing with system uncer- tainties. When compared with the traditional received signal strength (RSS)-based handover scheme, the proposed scheme reduces the task execution latency by about 30%. Second, fixed edge servers that are sparsely deployed around mobile UEs are not flexible enough to deal with time-varying task offloading. Dispatching mobile servers is formulated as a variable-sized bin-packing problem with geographic constraints. A novel online unmanned aerial vehicle (UAV)-mounted edge server dispatching scheme is proposed to provide flexible mobile-to-mobile edge computing services. UAVs are dispatched to the appropriate hover locations by identifying the hot-spot areas sequen- tially. Theoretical analysis is provided with the worst-case performance guarantee. Extensive evaluations driven by real-world mobile requests show that, with a given task finish time, the mobile dispatching scheme can serve 59% more users on aver- age when compared with the fixed deployment. In addition, the server utilization reaches 98% during the daytime with intensive task requests. Utilizing both the fixed and mobile edge servers can satisfy even more UE demands with fewer UAVs to be dispatched and a better server utilization. To sum up, not only the communication condition but also the computation lim- itation have an impact on the edge server selection and mobility management in MEC. Moreover, dispatching mobile edge servers can be an effective and flexible way to supplement the fixed servers and deal with dynamic offloading requests. / Graduate

Today more devices are being connected to the Internet via mobile networks. With more devices in mobile networks, the workload on radio base stations increases. Radio base stations must be energy efficient and cheap which makes high-performance central processing units (CPUs) a bad alternative to meet the increasing workload. An alternative could be a graphics processing unit (GPU) which have a different hardware architecture more suitable for data parallel problems. This thesis has investigated the parallelisation possibilities in the user-equipment handling part of radio base stations, and the aim was to use a GPU to take advantage of the parallelism. The investigation found a mixed pipeline and data parallelism in user-equipment handling. A parallelism suitable for a graphics processing unit (GPU) execution. The tasks which handle user-equipment were divided into smaller communication-free sub-tasks. Sub-task batches of user-equipment were collected and offloaded to a GPU. A peak throughput gain of 62.2 times over the single-threaded CPU was achieved, but with an impact on latency with more than a magnitude. The latency was for all workloads at least 1.24 higher for the GPU implementations compared to the CPU implementations. A radio base station with many more user-equipment than the once existing today was simulated. For this radio base station, a gain of 14.0 times the single-threaded CPU was achieved, while the latency increased by 2.4 times. To really make use of a GPU implementation the number of user-equipment, the load, must be higher than in existing radio base stations today.

Drone usage is increasing, both in recreational use and in the industry. With it comes a number of problems to tackle. Primarily, there are certain areas in which flying drones pose a security threat, e.g., around airports or other no-fly zones. Other problems can appear when there are drones in mobile networks which can cause interference. Such interference comes from the fact that radio transmissions emitted from drones can travel more freely than those from regular UEs (User Equipment) on the ground since there are few obstructions in the air. Additionally, the data traffic sent from drones is often high volume in the form of video streams. The goal of this thesis is to identify so-called "rogue drones" connected to an LTE network. Rogue drones are flying drones that appear to be regular UEs in the network. Drone identification is a binary classification problem where UEs in a network are classified as either a drone or a regular UE and this thesis proposes machine learning methods that can be used to solve it. Classifications are based on radio measurements and statistics reported by UEs in the network. The data for the work in this thesis is gathered through simulations of a heterogenous LTE network in an urban scenario. The primary idea of this thesis is to use a type of cascading classifier, meaning that classifications are made in a series of stages with increasingly complex models where only a subset of examples are passed forward to subsequent stages. The motivation for such a structure is to minimize the computational requirements at the entity making the classifications while still being complex enough to achieve high accuracy. The models explored in this thesis are two-stage cascading classifiers using decision trees and ensemble learning techniques. It is found that close to 60% of the UEs in the dataset can be classified without errors in the first of the two stages. The rest is forwarded to a more complex model which requires more data from the UEs and can achieve up to 98% accuracy.

Emerging 5G mobile networks are envisioned to become multi-service environments, enabling the dynamic deployment of services with a diverse set of performance requirements, accommodating the needs of mobile network operators, verticals and over-the-top service providers. The Radio Access Network (RAN) part of mobile networks is expected to play a very significant role towards this evolution. Unfortunately, such a vision cannot be efficiently supported by the conventional RAN architecture, which adopts a fixed and rigid design. For the network to evolve, flexibility in the creation, management and control of the RAN components is of paramount importance. The key elements that can allow us to attain this flexibility are the programmability and the virtualization of the network functions. While in the case of the mobile core, these issues have been extensively studied due to the advent of technologies like Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) and the similarities that the core shares with other wired networks like data centers, research in the domain of the RAN is still in its infancy. The contributions made in this thesis significantly advance the state of the art in the domain of RAN programmability and virtualization in three dimensions. First, we design and implement a software-defined RAN (SD-RAN) platform called FlexRAN, that provides a flexible control plane designed with support for real-time RAN control applications, flexibility to realize various degrees of coordination among RAN infrastructure entities, and programmability to adapt control over time and easier evolution to the future following SDN/NFV principles. Second, we leverage the capabilities of the FlexRAN platform to design and implement Orion, which is a novel RAN slicing system that enables the dynamic on-the-fly virtualization of base stations, the flexible customization of slices to meet their respective service needs and which can be used in an end-to-end network slicing setting. Third, we focus on the use case of multi-tenancy in a neutral-host indoors small-cell environment, where we design Iris, a system that builds on the capabilities of FlexRAN and Orion and introduces a dynamic pricing mechanism for the efficient and flexible allocation of shared spectrum to the tenants. A number of additional use cases that highlight the benefits of the developed systems are also presented. The lessons learned through this research are summarized and a discussion is made on interesting topics for future work in this domain. The prototype systems presented in this thesis have been made publicly available and are being used by various research groups worldwide in the context of 5G research.

Les réseaux mobiles 4G basés sur la norme LTE (Long Term Evolution), sont des réseaux tout IP. Les différents problèmes de transport IP comme le retard, la gigue et la perte despaquets peuvent fortement dégrader la qualité des communications temps réel telles que la téléphonie. Les opérateurs ont mis en oeuvre des mécanismes d’optimisation du transport de la voix dans le réseau afin d'améliorer la qualité perçue. Cependant, les algorithmes propriétaires de gestion de la qualité dans les terminaux ne sont pas spécifiés dans les standards. Dans ce contexte, nous nous intéressons aux mécanismes d'adaptation de média, intégrés dans les terminaux afin d'améliorer la qualité d’expérience (QoE). En particulier, nous évaluons de manière expérimentale des métriques QoE de la voix sur LTE (VoLTE) en utilisant une méthode de test standardisée. Nous proposons d’améliorer la méthode de test et discutons la manière dont cette méthode peut être étendue pour évaluer les performances du buffer de gigue. Nous évaluons également de manière expérimentale la qualité de WebRTC dans différentes conditions radios en utilisant un réseau réel. Nous évaluons l'impact du buffer de gigue et de la variation du débit sur la qualité mesurée. Pour améliorer la robustesse des codecs contre la perte de paquets, nous proposons d’utiliser une redondance simple au niveau applicatif. Nous implémentons cette redondance pour le codec EVS (Enhanced Voice Service) et nous évaluons ses performances. Enfin, nous proposons un protocole de signalisation qui permet d’envoyer des requêtes de redondance au cours d’une communication afin d’activer ou désactiver celle-ci dynamiquement. / Fourth-generation mobile networks, based on the Long Term Evolution (LTE) standard, are all- IP networks. Thus, mobile telephony providers are facing new types of quality degradations related to the voice packet transport over IP network such as delay, jitter and packet loss. These factors can heavily degrade voice communications quality. The real-time constraint of such services makes them highly sensitive to delay and loss. Network providers have implemented several network optimizations for voice transport to enhance perceived quality. However, the proprietary quality management algorithms implemented in terminals are left unspecified in the standards. In this context, we are interested in media adaptation mechanisms integrated in terminals to enhance the overall Quality of Experience (QoE). In particular, we experimentally evaluate Voice over LTE (VoLTE) QoE metrics such as delay and Mean Opinion Score (MOS) sing a standardized test method. We propose some enhancements to the actual test method and discuss how this method can be extended to evaluate de-jitter buffer performance. We also experimentally evaluate WebRTC voice quality in different radio conditions using a realLTE test network. We evaluate the impact of jitter buffer and bit rate variations on the measured quality. To enhance voice codec robustness against packet loss, we propose a simple application layer redundancy. We implemented it for the Enhanced Voice Service (EVS) codec and evaluate it. Finally, we propose a signaling protocol that allows sending redundancy requests during a call to dynamically activate or deactivate the redundancy mechanism.

<p>Ova disertacija se bavi istraživanjem problema kontinuiteta IP<br />mrežnih sesija u oblasti komunikscija u mobilnim računarskim mrežama.<br />Cilj istraživanja u okviru ove doktorske disertacije je da se definiše<br />rešenje problema mobilnosti primenjivo na heterogene bežične mreže<br />primenom metode softverski definisanog umrežavanja. U okviru<br />istraživanja prikazana je i praktična implementacija predloženog<br />rešenja. Tokom istraživanja su dobijeni rezultati koji ukazuju na potrebu<br />integracije postojećih tradicionalnih bežičnih mreža sa softverski<br />definisanim mrežama. Osnovu predloženog rešenja predstavlja<br />inkrementslan pristup u pogledu uvođenja novih SDN funkcionslnosti u<br />bežične IP mreže. Kroz implementaciju minimalnog seta SDN<br />funkcionalnosti gradi se tzv. hibridni model SDN mreže. Glavni<br />doprinos ovog istraživanja se ogleda u definisanju postupka koji će<br />omogućiti da se prevaziđe problem mobilnosti u aktuelnom konceptu<br />heterogenih bežičnih računarskih mreža. Ovakav model rešenja, pruža<br />značajan doprinos i sa aspekta ulaganja u promenu infrastrukture u<br />bežičnim mrežama. Implementacijom hibridnog modela, redukuje se<br />potreba za potpunim, ali i značajnim, uvođenjem virtuelne<br />infrastrukture bazirane na fleksibilnim softverski definisanim<br />mrežama.</p> / <p>This dissertation investigates the problem of IP networking communication<br />sessions continuity in mobile computer networks. The aim of the research within<br />this doctoral dissertation is to define a solution to the mobility problem<br />applicable to heterogeneous wireless networks using the software-defined<br />networking method. The research also demonstrates the practical<br />implementation of the proposed solution. During the research were obtained<br />results that indicate the need for integration of software-defined networks into<br />existing traditional wireless networks. The basis of the proposed solution is an<br />incremental approach in terms of introducing new SDN functionality into<br />wireless IP networks. Through the implementation of the minimal set of SDN<br />functionality, the so-called hybrid model of the SDN network is being built. The<br />main contribution of this research is reflected in the definition of a process that<br />will allow to overcome the problem of mobility in the current concept of<br />heterogeneous wireless computing networks. This solution model, also provides<br />a significant contribution from the aspect of investing in the change of<br />infrastructure in wireless networks. Implementation of the hybrid model reduces<br />the need for a complete replacement with a virtual infrastructure based on<br />flexible software-defined networks.</p>

Users (or software agents) are served by multiple networked terminal devices, each of which may in turn have multiple network interfaces. This multi-homing at both ???user??? and ???device??? level presents new opportunities for mobility handling. Mobility may be handled by switching ongoing application data streams between devices, by utilising intermediary adaptation or connectivity enhancement services, or both. However this requires middleware support that is not provided by current systems. This thesis presents a set of integrated solutions to enable this kind of mobility handling, based on concept of Personal Networks (PN). Personal Networks (PN) consist of dynamic conglomerations of terminal and service devices tasked to facilitate the delivery of information to and from a single focal point, which may be a human user or software agent. This concept creates the potential to view mobility handling as a path selection problem, since there may be multiple valid terminal device and service proxy configurations that can successfully carry a given communication session from one PN to another PN. Depending on context, it may be necessary to switch between paths. To this end, this thesis proposes and evaluates a set of inter-dependent mechanisms to facilitate the discovery and use of different candidate end-to-end paths. The proposal comprises mechanisms for secure inter-device mobility using delegated cryptographic identifiers, autonomous service proxy selection and composition, and distributed resolution of cryptographic identifiers to lower layer addresses.