Distributed Resource Allocation and Performance Analysis in 5G Wireless Cellular Networks

This thesis focuses on the study of Heterogeneous Networks (HetNets), Device-to-device (D2D) communication networks, and unmanned aerial vehicle (UAV) networks in fifth generation wireless communication (5G) systems. HetNets that consist of macro-cells and small-cells have become increasingly popular in current wireless networks and 5G systems to meet the exponentially growing demand for higher data rates. Compared to conventional homogeneous cellular networks, the disparity of transmission power among different types of base stations (BSs), the relatively random deployment of SBSs, and the densifying networks, bring new challenges, such as the imbalanced load between macro and small cells and severe inter-cell interference. In the other hand, with the skyrocketing number of tablets and smart phones, the notion of caching popular content in the storage of BSs and users' devices is proposed to reduce duplicated wireless transmissions. To fulfill multi-fold communication requirements from humans, machine, and things, the 5G systems which include D2D communications, UAV communications, and so on, can improve the network performance. Among them, the performance analyses of these emerging technologies are attracting much attention and should be investigated first. This thesis focuses on these hot issues and emerging technologies in 5G systems, analyzing the network performance and conducting the allocation of available resources, such as serving BSs, spectrum resources, and storage resources. Specifically, three main research focuses are included in the thesis. The first focus of this thesis is the impact of the BS idle mode capacity (IMC) on the network performance of multi-tier and dense HCNs with both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions. I consider a more practical set-up with a finite number of UEs in the analysis. Moreover, the SBSs apply a positive power bias in the cell association procedure, so that macrocell UEs are actively encouraged to use the more lightly loaded SBSs. In addition, to address the severe interference that these cell range expanded UEs may suffer, the MBSs apply enhanced inter-cell interference coordination (eICIC), in the form of almost blank subframe (ABS) mechanism. For this model, I derive the coverage probability and the rate of a typical UE in the whole network or a certain tier. The impact of the IMC on the performance of the network is shown to be significant. In particular, it is important to note that there will be a surplus of BSs when the BS density exceeds the UE density, and thus a large number of BSs switch off. As a result, the overall coverage probability, as well as the area spectral efficiency (ASE), will continuously increase with the BS density, addressing the network outage that occurs when all BSs are active and the interference becomes LoS dominated. Finally, the optimal ABS factors are investigated in different BS density regions. One of major findings is that MBSs should give up all resources in favor of the SBSs when the small cell networks go ultra-dense. This reinforces the need for orthogonal deployments, shedding new light on the design and deployment of the future 5G dense HCNs. The second focus of this thesis is the content caching in D2D communication networks. In practical deployment, D2D content caching has its own problem that is not all of the user devices are willing to share the content with others due to numerous concerns such as security, battery life, and social relationship. To solve this problem, I consider the factor of social relationship in the deployment of D2D content caching. First, I apply stochastic geometry theory to derive an analytical expression of downloading performance for the D2D caching network. Specifically, a social relationship model with respect to the physical distance is adopted in the analysis to obtain the average downloading delay performance using random and deterministic caching strategies. Second, to achieve a better performance in more practical and specific scenarios, I develop a socially aware distributed caching strategy based on a decentralized learning automaton, to optimize the cache placement operation in D2D networks. Different from the existing caching schemes, the proposed algorithm not only considers the file request probability and the closeness of devices as measured by their physical distance, but also takes into account the social relationship between D2D users. The simulation results show that the proposed algorithm can converge quickly and outperforms the random and deterministic caching strategies. With these results, the work sheds insights on the design of D2D caching in the practical deployment of 5G networks. The third focus of this thesis is the performance analysis for practical UAV-enabled networks. By considering both LoS and NLoS transmissions between aerial BSs and ground users, the coverage probability and the ASE are derived. Considering that there is no consensus on the path loss model for studying UAVs in the literature, in this focus, three path loss models, i.e., high-altitude model, low-altitude model, and ultra-low-altitude model, are investigated and compared. Moreover, the lower bound of the network performance is obtained assuming that UAVs are hovering randomly according to homogeneous Poisson point process (HPPP), while the upper bound is derived assuming that UAVs can instantaneously move to the positions directly overhead ground users. From the analytical and simulation results for a practical UAV height of 50 meters, I find that the network performance of the high-altitude model and the low-altitude model exhibit similar trends, while that of the ultra-low-altitude model deviates significantly from the above two models. In addition, the optimal density of UAVs to maximize the coverage probability performance has also been investigated

Novel applications and contexts for the cognitive packet network

Autonomic communication, which is the development of self-configuring, self-adapting, self-optimising and self-healing communication systems, has gained much attention in the network research community. This can be explained by the increasing demand for more sophisticated networking technologies with physical realities that possess computation capabilities and can operate successfully with minimum human intervention. Such systems are driving innovative applications and services that improve the quality of life of citizens both socially and economically. Furthermore, autonomic communication, because of its decentralised approach to communication, is also being explored by the research community as an alternative to centralised control infrastructures for efficient management of large networks. This thesis studies one of the successful contributions in the autonomic communication research, the Cognitive Packet Network (CPN). CPN is a highly scalable adaptive routing protocol that allows for decentralised control in communication. Consequently, CPN has achieved significant successes, and because of the direction of research, we expect it to continue to find relevance. To investigate this hypothesis, we research new applications and contexts for CPN. This thesis first studies Information-Centric Networking (ICN), a future Internet architecture proposal. ICN adopts a data-centric approach such that contents are directly addressable at the network level and in-network caching is easily supported. An optimal caching strategy for an information-centric network is first analysed, and approximate solutions are developed and evaluated. Furthermore, a CPN inspired forwarding strategy for directing requests in such a way that exploits the in-network caching capability of ICN is proposed. The proposed strategy is evaluated via discrete event simulations and shown to be more effective in its search for local cache hits compared to the conventional methods. Finally, CPN is proposed to implement the routing system of an Emergency Cyber-Physical System for guiding evacuees in confined spaces in emergency situations. By exploiting CPN’s QoS capabilities, different paths are assigned to evacuees based on their ongoing health conditions using well-defined path metrics. The proposed system is evaluated via discrete-event simulations and shown to improve survival chances compared to a static system that treats evacuees in the same way.Open Acces

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

D4.2 Intelligent D-Band wireless systems and networks initial designs

This deliverable gives the results of the ARIADNE project's Task 4.2: Machine Learning based network intelligence. It presents the work conducted on various aspects of network management to deliver system level, qualitative solutions that leverage diverse machine learning techniques. The different chapters present system level, simulation and algorithmic models based on multi-agent reinforcement learning, deep reinforcement learning, learning automata for complex event forecasting, system level model for proactive handovers and resource allocation, model-driven deep learning-based channel estimation and feedbacks as well as strategies for deployment of machine learning based solutions. In short, the D4.2 provides results on promising AI and ML based methods along with their limitations and potentials that have been investigated in the ARIADNE project

Atomic Transfer for Distributed Systems

Building applications and information systems increasingly means dealing with concurrency and faults stemming from distribution of system components. Atomic transactions are a well-known method for transferring the responsibility for handling concurrency and faults from developers to the software\u27s execution environment, but incur considerable execution overhead. This dissertation investigates methods that shift some of the burden of concurrency control into the network layer, to reduce response times and increase throughput. It anticipates future programmable network devices, enabling customized high-performance network protocols. We propose Atomic Transfer (AT), a distributed algorithm to prevent race conditions due to messages crossing on a path of network switches. Switches check request messages for conflicts with response messages traveling in the opposite direction. Conflicting requests are dropped, obviating the request\u27s receiving host from detecting and handling the conflict. AT is designed to perform well under high data contention, as concurrency control effort is balanced across a network instead of being handled by the contended endpoint hosts themselves. We use AT as the basis for a new optimistic transactional cache consistency algorithm, supporting execution of atomic applications caching shared data. We then present a scalable refinement, allowing hierarchical consistent caches with predictable performance despite high data update rates. We give detailed I/O Automata models of our algorithms along with correctness proofs. We begin with a simplified model, assuming static network paths and no message loss, and then refine it to support dynamic network paths and safe handling of message loss. We present a trie-based data structure for accelerating conflict-checking on switches, with benchmarks suggesting the feasibility of our approach from a performance stand-point

When things matter: A survey on data-centric Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, but several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy and continuous. This paper reviews the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

Plugging in trust and privacy : three systems to improve widely used ecosystems

The era of touch-enabled mobile devices has fundamentally changed our communication habits. Their high usability and unlimited data plans provide the means to communicate any place, any time and lead people to publish more and more (sensitive) information. Moreover, the success of mobile devices also led to the introduction of new functionality that crucially relies on sensitive data (e.g., location-based services). With our today’s mobile devices, the Internet has become the prime source for information (e.g., news) and people need to rely on the correctness of information provided on the Internet. However, most of the involved systems are neither prepared to provide robust privacy guarantees for the users, nor do they provide users with the means to verify and trust in delivered content. This dissertation introduces three novel trust and privacy mechanisms that overcome the current situation by improving widely used ecosystems. With WebTrust we introduce a robust authenticity and integrity framework that provides users with the means to verify both the correctness and authorship of data transmitted via HTTP. X-pire! and X-pire 2.0 offer a digital expiration date for images in social networks to enforce post-publication privacy. AppGuard enables the enforcement of fine-grained privacy policies on third-party applications in Android to protect the users privacy.Heutige Mobilgeräte mit Touchscreen haben unsere Kommunikationsgewohnheiten grundlegend geändert. Ihre intuitive Benutzbarkeit gepaart mit unbegrenztem Internetzugang erlaubt es uns jederzeit und überall zu kommunizieren und führt dazu, dass immer mehr (vertrauliche) Informationen publiziert werden. Des Weiteren hat der Erfolg mobiler Geräte zur Einführung neuer Dienste die auf vertraulichen Daten aufbauen (z.B. positionsabhängige Dienste) beigetragen. Mit den aktuellen Mobilgeräten wurde zudem das Internet die wichtigste Informationsquelle (z.B. für Nachrichten) und die Nutzer müssen sich auf die Korrektheit der von dort bezogenen Daten verlassen. Allerdings bieten die involvierten Systeme weder robuste Datenschutzgarantien, noch die Möglichkeit die Korrektheit bezogener Daten zu verifizieren. Diese Dissertation führt drei neue Mechanismen für das Vertrauen und den Datenschutz ein, die die aktuelle Situation in weit verbreiteten Systemen verbessern. WebTrust, ein robustes Authentizitäts- und Integritätssystem ermöglicht es den Nutzern sowohl die Korrektheit als auch die Autorenschaft von über HTTP übertragenen Daten zu verifizieren. X-pire! und X-pire 2.0 bieten ein digitales Ablaufdatum für Bilder in sozialen Netzwerken um Daten auch nach der Publikation noch vor Zugriff durch Dritte zu schützen. AppGuard ermöglicht das Durchsetzen von feingranularen Datenschutzrichtlinien für Drittanbieteranwendungen in Android um einen angemessen Schutz der Nutzerdaten zu gewährleisten

Plugging in trust and privacy : three systems to improve widely used ecosystems

The era of touch-enabled mobile devices has fundamentally changed our communication habits. Their high usability and unlimited data plans provide the means to communicate any place, any time and lead people to publish more and more (sensitive) information. Moreover, the success of mobile devices also led to the introduction of new functionality that crucially relies on sensitive data (e.g., location-based services). With our today’s mobile devices, the Internet has become the prime source for information (e.g., news) and people need to rely on the correctness of information provided on the Internet. However, most of the involved systems are neither prepared to provide robust privacy guarantees for the users, nor do they provide users with the means to verify and trust in delivered content. This dissertation introduces three novel trust and privacy mechanisms that overcome the current situation by improving widely used ecosystems. With WebTrust we introduce a robust authenticity and integrity framework that provides users with the means to verify both the correctness and authorship of data transmitted via HTTP. X-pire! and X-pire 2.0 offer a digital expiration date for images in social networks to enforce post-publication privacy. AppGuard enables the enforcement of fine-grained privacy policies on third-party applications in Android to protect the users privacy.Heutige Mobilgeräte mit Touchscreen haben unsere Kommunikationsgewohnheiten grundlegend geändert. Ihre intuitive Benutzbarkeit gepaart mit unbegrenztem Internetzugang erlaubt es uns jederzeit und überall zu kommunizieren und führt dazu, dass immer mehr (vertrauliche) Informationen publiziert werden. Des Weiteren hat der Erfolg mobiler Geräte zur Einführung neuer Dienste die auf vertraulichen Daten aufbauen (z.B. positionsabhängige Dienste) beigetragen. Mit den aktuellen Mobilgeräten wurde zudem das Internet die wichtigste Informationsquelle (z.B. für Nachrichten) und die Nutzer müssen sich auf die Korrektheit der von dort bezogenen Daten verlassen. Allerdings bieten die involvierten Systeme weder robuste Datenschutzgarantien, noch die Möglichkeit die Korrektheit bezogener Daten zu verifizieren. Diese Dissertation führt drei neue Mechanismen für das Vertrauen und den Datenschutz ein, die die aktuelle Situation in weit verbreiteten Systemen verbessern. WebTrust, ein robustes Authentizitäts- und Integritätssystem ermöglicht es den Nutzern sowohl die Korrektheit als auch die Autorenschaft von über HTTP übertragenen Daten zu verifizieren. X-pire! und X-pire 2.0 bieten ein digitales Ablaufdatum für Bilder in sozialen Netzwerken um Daten auch nach der Publikation noch vor Zugriff durch Dritte zu schützen. AppGuard ermöglicht das Durchsetzen von feingranularen Datenschutzrichtlinien für Drittanbieteranwendungen in Android um einen angemessen Schutz der Nutzerdaten zu gewährleisten