Infrastructure-less D2D Communications through Opportunistic Networks

Mención Internacional en el título de doctorIn recent years, we have experienced several social media blackouts, which have shown how much our daily experiences depend on high-quality communication services. Blackouts have occurred because of technical problems, natural disasters, hacker attacks or even due to deliberate censorship actions undertaken by governments. In all cases, the spontaneous reaction of people consisted in finding alternative channels and media so as to reach out to their contacts and partake their experiences. Thus, it has clearly emerged that infrastructured networks—and cellular networks in particular—are well engineered and have been extremely successful so far, although other paradigms should be explored to connect people. The most promising of today’s alternative paradigms is Device-to-Device (D2D) because it allows for building networks almost freely, and because 5G standards are (for the first time) seriously addressing the possibility of using D2D communications. In this dissertation I look at opportunistic D2D networking, possibly operating in an infrastructure-less environment, and I investigate several schemes through modeling and simulation, deriving metrics that characterize their performance. In particular, I consider variations of the Floating Content (FC) paradigm, that was previously proposed in the technical literature. Using FC, it is possible to probabilistically store information over a given restricted local area of interest, by opportunistically spreading it to mobile users while in the area. In more detail, a piece of information which is injected in the area by delivering it to one or more of the mobile users, is opportunistically exchanged among mobile users whenever they come in proximity of one another, progressively reaching most (ideally all) users in the area and thus making the information dwell in the area of interest, like in a sort of distributed storage. While previous works on FC almost exclusively concentrated on the communication component, in this dissertation I look at the storage and computing components of FC, as well as its capability of transferring information from one area of interest to another. I first present background work, including a brief review of my Master Thesis activity, devoted to the design, implementation and validation of a smartphone opportunistic information sharing application. The goal of the app was to collect experimental data that permitted a detailed analysis of the occurring events, and a careful assessment of the performance of opportunistic information sharing services. Through experiments, I showed that many key assumptions commonly adopted in analytical and simulation works do not hold with current technologies. I also showed that the high density of devices and the enforcement of long transmission ranges for links at the edge might counter-intuitively impair performance. The insight obtained during my Master Thesis work was extremely useful to devise smart operating procedures for the opportunistic D2D communications considered in this dissertation. In the core of this dissertation, initially I propose and study a set of schemes to explore and combine different information dissemination paradigms along with real users mobility and predictions focused on the smart diffusion of content over disjoint areas of interest. To analyze the viability of such schemes, I have implemented a Python simulator to evaluate the average availability and lifetime of a piece of information, as well as storage usage and network utilization metrics. Comparing the performance of these predictive schemes with state-of-the-art approaches, results demonstrate the need for smart usage of communication opportunities and storage. The proposed algorithms allow for an important reduction in network activity by decreasing the number of data exchanges by up to 92%, requiring the use of up to 50% less of on-device storage, while guaranteeing the dissemination of information with performance similar to legacy epidemic dissemination protocols. In a second step, I have worked on the analysis of the storage capacity of probabilistic distributed storage systems, developing a simple yet powerful information theoretical analysis based on a mean field model of opportunistic information exchange. I have also extended the previous simulator to compare the numerical results generated by the analytical model to the predictions of realistic simulations under different setups, showing in this way the accuracy of the analytical approach, and characterizing the properties of the system storage capacity. I conclude from analysis and simulated results that when the density of contents seeded in a floating system is larger than the maximum amount which can be sustained by the system in steady state, the mean content availability decreases, and the stored information saturates due to the effects of resource contention. With the presence of static nodes, in a system with infinite host memory and at the mean field limit, there is no upper bound to the amount of injected contents which a floating system can sustain. However, as with no static nodes, by increasing the injected information, the amount of stored information eventually reaches a saturation value which corresponds to the injected information at which the mean amount of time spent exchanging content during a contact is equal to the mean duration of a contact. As a final step of my dissertation, I have also explored by simulation the computing and learning capabilities of an infrastructure-less opportunistic communication, storage and computing system, considering an environment that hosts a distributed Machine Learning (ML) paradigm that uses observations collected in the area over which the FC system operates to infer properties of the area. Results show that the ML system can operate in two regimes, depending on the load of the FC scheme. At low FC load, the ML system in each node operates on observations collected by all users and opportunistically shared among nodes. At high FC load, especially when the data to be opportunistically exchanged becomes too large to be transmitted during the average contact time between nodes, the ML system can only exploit the observations endogenous to each user, which are much less numerous. As a result, I conclude that such setups are adequate to support general instances of distributed ML algorithms with continuous learning, only under the condition of low to medium loads of the FC system. While the load of the FC system induces a sort of phase transition on the ML system performance, the effect of computing load is more progressive. When the computing capacity is not sufficient to train all observations, some will be skipped, and performance progressively declines. In summary, with respect to traditional studies of the FC opportunistic information diffusion paradigm, which only look at the communication component over one area of interest, I have considered three types of extensions by looking at the performance of FC: over several disjoint areas of interest; in terms of information storage capacity; in terms of computing capacity that supports distributed learning. The three topics are treated respectively in Chapters 3 to 5.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Claudio Ettori Casetti.- Secretario: Antonio de la Oliva Delgado.- Vocal: Christoph Somme

Towards reliable geographic broadcasting in vehicular networks

In Vehicular ad hoc Networks (VANETs), safety-related messages are broadcasted amongst cars, helping to improve drivers' awareness of the road situation. VANETs’ reliability are highly affected by channel contention. This thesis first addresses the issue of channel use efficiency in geographical broadcasts (geocasts). Constant connectivity changes inside a VANET make the existing routing algorithms unsuitable. This thesis presents a geocast algorithm that uses a metric to estimate the ratio of useful to useless packet received. Simulations showed that this algorithm is more channel-efficient than the farthest-first strategy. It also exposes a parameter, allowing it to adapt to channel load. Second, this thesis presents a method of estimating channel load for providing feedback to moderate the offered load. A theoretical model showing the relationship between channel load and the idle time between transmissions is presented and used to estimate channel contention. Unsaturated stations on the network were shown to have small but observable effects on this relationship. In simulations, channel estimators based on this model show higher accuracy and faster convergence time than by observing packet collisions. These estimators are also less affected by unsaturated stations than by observing packet collisions. Third, this thesis couples the channel estimator to the geocast algorithm, producing a closed-loop load-reactive system that allows geocasts to adapt to instantaneous channel conditions. Simulations showed that this system is not only shown to be more efficient in channel use and be able to adapt to channel contention, but is also able to self-correct suboptimal retransmission decisions. Finally, this thesis demonstrates that all tested network simulators exhibit unexpected behaviours when simulating broadcasts. This thesis describes in depth the error in ns-3, leading to a set of workarounds that allows results from most versions of ns-3 to be interpreted correctly

Cognitive-Empowered Femtocells: An Intelligent Paradigm of a Robust and Efficient Media Access

Driven by both the need for ubiquitous wireless services and the stringent strain on radio spectrum faced in today's wireless communications, cognitive radio (CR) have been investigated as a promising solution to deploy Wireless Regional Area Networks (WRANs) for an efficient spectrum utilization. Communication devices with CR capabilities are able to access spectrum bands licensed for other wireless services in an opportunistic and secondary fashion, while preventing harmful interference to incumbent licensed services. However, a lesson learned from early experiences in developing such macro-cellular networks is that it becomes increasingly less economically viable to develop CR macrocellular infrastructures for increasing data rates in both line-of-sight as well as non-line-of-sight situation of WRAN, and the corresponding quality of service (QoS) in macrocellular networks is also noticeably degraded due to path loss, shadowing, and multipath fading due to wall penetration. Moreover, there are several challenges to make the real-world CR enabling dynamic spectrum access a difficult problem to implement without harmful interference. First, the hardware design of cognitive radio on the physical layer involves the tuning over a broad range of spectrum to detect a weak signal in a dynamic environment of fading channels, which in turn makes identification of the spectrum opportunities hard to achieve in an efficient and accurate manner. Second, opportunistic media access based on imperfect spectrum usage information obtain from physical layer brings up undesirable interference issue, as well as reliability issues introduced by mutual interference. Third, the curial issue is to determine which channels to use for data transmissions in presence of the dynamic and opportunistic nature of wireless environments, in the case where pre-defined dedicated control channel is not available in the complex and heterogenous networks. In this dissertation, a novel framework called Cognitive-Empowered Femtocell (CEF), which combines CR techniques with femtocell networking, is introduced to tackle these challenges and achieve better spectrum reuse, lower interference, easy integration, wider network coverage, as well as fast and cost effective early stage WRAN. In this framework, a sensing coordination scheme is proposed to gracefully unshackles the master/slave relationship between central controllers and end users, while maintaining order and coordination such that better sensing precision and efficiency can be achieved. As such, the network intelligence can be expanded from controlling the intelligence paradigm to better understand the satisfy wireless user needs. We also discuss design and deployment aspects such as sensing with reasoning approach, gossip-enabled stochastic media access without a dedicated control channel, all of which are important to the success of the CEF framework. We illustrate that such a framework allows wireless users to intelligently capture spectrum opportunities while mitigating interference to other users, as well as improving the network capacity. Performance analysis and simulations were conducted based on these techniques to provide insight on the future direction of interference suppression for dynamic spectrum access

Energy-aware Gossip Protocol for Wireless Sensor Networks

Dissertação de mestrado em Engenharia InformáticaIn Wireless Sensor Networks (WSNs), typically composed of nodes with resource constraints, leveraging efficient processes is crucial to enhance the network longevity and consequently the sustainability in ultra-dense and heterogeneous environments, such as smart cities. Epidemic algorithms are usually efficient in delivering packets to a sink or to all it’s peers but have poor energy efficiency due to the amount of packet redundancy. Directional algorithms, such as Minimum Cost Forward Algorithm (MCFA) or Directed Diffusion, yield high energy efficiency but fail to handle mobile environments, and have poor network coverage. This work proposes a new epidemic algorithm that uses the current energy state of the network to create a topology that is cyclically updated, fault tolerant, whilst being able to handle the challenges of a static or mobile heterogeneous network. Depending on the application, tuning in the protocol settings can be made to prioritise desired characteristics. The proposed protocol has a small computational footprint and the required memory is proportional not to the size of the network, but to the number of neighbours of a node, enabling high scalability. The proposed protocol was tested, using a ESP8266 as an energy model reference, in a simulated environment with ad-hoc wireless nodes. It was implemented at the application level with UDP sockets, and resulted in a highly energy efficient protocol, capable of leveraging extended network longevity with different static or mobile topologies, with results comparable to a static directional algorithm in delivery efficiency.Em Redes de Sensores sem Fios (RSF), tipicamente compostas por nós com recursos lim-itados, alavancar processos eficientes é crucial para aumentar o tempo de vida da rede e consequentemente a sustentabilidade em ambientes heterogéneos e ultra densos, como cidades inteligentes por exemplo. Algoritmos epidêmicos são geralmente eficientes em en-tregar pacotes para um sink ou para todos os nós da rede, no entanto têm baixa eficiência energética devido a alta taxa de duplicação de pacotes. Algoritmos direcionais, como o MCFA ou de Difusão Direta, rendem alta eficiência energética mas não conseguem lidar com ambientes móveis, e alcançam baixa cobertura da rede. Este trabalho propõe um novo protocolo epidêmico que faz uso do estado energético atual da rede para criar uma topologia que por sua vez atualizada ciclicamente, tolerante a falhas, ao mesmo tempo que é capaz de lidar com os desafios de uma rede heterogênea estática ou móvel. A depender da aplicação, ajustes podem ser feitos às configurações do protocolo para que o mesmo priorize determinadas características. O protocolo proposto tem um pequeno impacto computacional e a memória requerida é proporcional somente à quantidade de vizinhos do nó, não ao tamanho da rede inteira, permitindo assim alta escalabilidade. O algoritmo proposto foi testado fazendo uso do modelo energético de uma ESP8266, em um ambiente simulado com uma rede sem fios ad-hoc. Foi implementado à nível aplicacional com sockets UDP, e resultou em um protocol energeticamente eficiente, capaz de disponibilizar alta longevidade da rede mesmo com diferentes topologias estáticas ou móveis com resultados comparáveis à um protocolo direcional em termos de eficiência na entrega de pacotes

Energy Efficiency of Distributed Signal Processing in Wireless Networks: A Cross-Layer Analysis

In order to meet the growing mobile data demand, future wireless networks will be equipped with a mulitude of access points (APs). Besides the important implications for the energy consumption, the trend towards densification requires the development of decentralized and sustainable radio resource management techniques. It is critically important to understand how the distribution of signal processing operations affects the energy efficiency of wireless networks. In this paper, we provide a cross-layer framework to evaluate and compare the energy efficiency of wireless networks under different levels of distribution of the signal processing load: 1) hybrid, where the signal processing operations are shared between nodes and APs; 2) centralized, where signal processing is entirely implemented at the APs; and 3) fully distributed, where all operations are performed by the nodes. We find that in practical wireless networks, hybrid signal processing exhibits a significant energy efficiency gain over both centralized and fully distributed approaches

Addressing Outdoor Throughput Sensitivity for Mobile Vehicles by Enhancing the VMESH MAC Protocol

To provide safe and efficient transportation, Vehicular Ad-Hoc Networks (VANETs) allow for the communication between a vehicle to another vehicle and for the communication between vehicles and stations near the road. As autonomous vehicles become closer to commercializing, the ability for moving vehicles to quickly and successfully send and receive packets becomes increasingly important. In this thesis, the 802.11p WAVE MAC protocol which was created specifically to address Vehicular Ad-Hoc Networks (VANETs), was analyzed. After reviewing existing models used to enhance throughput, the VMESH protocol was found to be better than the legacy WAVE MAC protocol. However, the VMESH protocol's channel allocation contention resolving scheme leads to a decreased throughput. This thesis proposes a new channel allocation scheme, Linear Modulus Autonomous Ordering (LMAO), that allows maximum channel utilization and therefore, an increased throughput. Given the number of cars in a system, the number of channels in a system, and the range of neighbors a car can see, the LMAO channel allocation methodology is found to perform significantly better than the VMESH and an upper bound approximated WAVE MAC channel allocation method

SO(2) Rotation Estimation in Camera Networks

This thesis focuses on the study of the localization problem in planar camera networks. Two distributed models for detecting the orientation of cameras are discussed and analyzed. The performance of these models is evaluated with respect to modifications in the network, such as the use of different communication protocols among agents and the change in the topology of the network. The theoretical findings are assessed via numerical simulations based on synthetic and experimental scenario

Improving forwarding mechanisms for mobile personal area networks

This thesis presents novel methods for improving forwarding mechanisms for personal area networks. Personal area networks are formed by interconnecting personal devices such as personal digital assistants, portable multimedia devices, digital cameras and laptop computers, in an ad hoc fashion. These devices are typically characterised by low complexity hardware, low memory and are usually batterypowered. Protocols and mechanisms developed for general ad hoc networking cannot be directly applied to personal area networks as they are not optimised to suit their specific constraints. The work presented herein proposes solutions for improving error control and routing over personal area networks, which are very important ingredients to the good functioning of the network. The proposed Packet Error Correction (PEC) technique resends only a subset of the transmitted packets, thereby reducing the overhead, while ensuring improved error rates. PEC adapts the number of re-transmissible packets to the conditions of the channel so that unnecessary retransmissions are avoided. It is shown by means of computer simulation that PEC behaves better, in terms of error reduction and overhead, than traditional error control mechanisms, which means that it is adequate for low-power personal devices. The proposed C2HR routing protocol, on the other hand, is designed such that the network lifetime is maximised. This is achieved by forwarding packets through the most energy efficient paths. C2HR is a hybrid routing protocol in the sense that it employs table-driven (proactive) as well as on-demand (reactive) components. Proactive routes are the primary routes, i.e., packets are forwarded through those paths when the network is stable; however, in case of failures, the protocol searches for alternative routes on-demand, through which data is routed temporarily. The advantage of C2HR is that data can still be forwarded even when routing is re-converging, thereby increasing the throughput. Simulation results show that the proposed routing method is more energy efficient than traditional least hops routing, and results in higher data throughput. C2HR relies on a network leader for collecting and distributing topology information, which in turn requires an estimate of the underlying topology. Thus, this thesis also proposes a new cooperative leader election algorithm and techniques for estimating network characteristics in mobile environments. The proposed solutions are simulated under various conditions and demonstrate appreciable behaviour

Efficient Multihop Wireless Communications in VANETs

Oggigiorno, una quota rilevante dei veicoli presenti sul mercato è dotata di notevoli capacità computazionali, sensoriali e cognitive. Questi veicoli ``intelligenti'' otterrebbero un beneficio ancora maggiore da queste potenzialità, attraverso l'impiego delle cosiddette comunicazioni inter-veicolari (Inter-Vehicular Communications, IVCs), un insieme di protocolli, standard e tecnologie in grado di dotare i veicoli di capacità comunicative. In particolare, grazie alle tecnologie IVCs, i veicoli possono creare reti decentralizzate, ed auto-organizzate, comunemente note come Vehicular Ad-hoc NETworks (VANETs). Quest'ultime possono essere formate, sia fra veicoli, determinando la realizzazione di comunicazioni inter-veicolari pure (Vehicle-to-Vehicle communications, V2V), oppure coinvolgendo anche nodi fissi (ad esempio, posti ai lati delle strade), determinando la realizzazione di comunicazioni da veicolo verso infrastruttura (Vehicle-to-Infrastructure, V2I), o da infrastruttura verso veicolo (Infrastructure-to-Vehicle I2V). In questa tesi presenteremo una famiglia di protocolli di instradamento a passi multipli, adatti per un largo spettro di applicazioni nell'ambito delle VANET, quali la prevenzione di incidenti stradali, o applicazioni di raccolta dati, in scenari di tipo V2V, V2I, o I2V. Il primo protocollo che viene proposto è un nuovo schema di broadcasting probabilistico per reti lineari a passi multipli, noto come Irresponsible Forwarding (IF), secondo il quale ogni veicolo decide probabilisticamente se effettuare la ritrasmissione (broadcast) di un messaggio ricevuto. La probabilità di ritrasmissione è determinata sulla base della propria distanza dalla sorgente e della densità spaziale dei propri vicini. I vantaggi principali del protocollo IF rispetto alle soluzioni presenti in letteratura, sono costituiti dalla sua natura intrinsecamente distribuita, dalla bassa latenza, e dall'assenza di overhead, in quanto esso non prevede l'utilizzo di pacchetti ausiliari di supporto Successivamente, presenteremo un secondo protocollo di instradamento probabilistico, noto come Silencing Irresponsible Forwarding (SIF), che riprendendo le idee alla base di IF, permette di ottenere una maggiore efficienza (e.g., un minore numero di ritrasmissioni), senza penalizzarne l'affidabilità, e mantenendo valori di latenza comparabili ad IF. In seguito, verrà inoltre proposto un protocollo di clustering decentralizzato, noto come Cluster-Head Election IF (CHE-IF). Quest'ultimo si propone di sfruttare lo spontaneo processo di formazione di cluster effimeri di nodi nelle reti veicolari, in maniera distribuita ed efficiente. Per ottenere questo risultato, CHE-IF utilizza l'idea alla base di IF, ma introducendo dei pacchetti di controllo aggiuntivi, espressamente dedicati alla realizzazione di cluster di nodi. Infine, le prestazioni di tutti i protocolli proposti verranno testate mediante simulazioni numeriche in realistici scenari veicolari, quali autostrade e strade urbane, assumendo di utilizzare interfacce radio compatibili con lo standard IEEE 802.11p.Nowadays, most of the vehicles available on the market are provided by sensorial, computational, and cognitive skills. Vehicles can achieve a higher awareness level, by exploiting these potentialities through Inter-Vehicular Communications (IVCs), a set of technologies that gives networking capabilities to the vehicles. Leveraging on the IVC technology, vehicles can create decentralized and self-organized vehicular networks, commonly denoted as Vehicular Ad-hoc NETworks (VANETs). These networks can be formed between vehicles, leading to Vehicle-to-Vehicle communications (V2V), or they can also involve some fixed network nodes (e.g., access points or road side unit) leading to the so-called Vehicle-to-Infrastructure (V2I) and Infrastructure-to-Vehicle (I2V) communications. In this thesis we present a family of multihop broadcast forwarding protocols suitable for a wide range of VANETs applications, ranging from accident-preventing, to data collection applications, in V2V, V2I, or I2V scenarios. The first proposed protocol is a new probabilistic-based broadcasting scheme for multi-hop linear networks, denoted as Irresponsible Forwarding (IF), where each vehicle probabilistically rebroadcasts a received data packet on the basis of (i) its distance from the source and (ii) the spatial density of its neighbors. The main advantages of the IF protocol with respect to solutions present in the literature, are its inherently distributed nature, the low-latency, and the absence of overhead, since auxiliary supporting packets are not needed. On the basis of the IF concept, we will present an improved probabilistic forwarding protocol, denoted as Silencing Irresponsible Forwarding (SIF) protocol, able to guarantee a greater efficiency (e.g., a smaller number of retransmissions), without penalizing the reliability, and maintaining a comparable latency. Furthermore, we will propose a novel decentralized clustering protocol, denoted as Cluster-Head Election IF (CHE-IF), whose goal is which of exploiting the spontaneous formation of ephemeral clusters of vehicles in VANETs, in a distributed and efficient manner. This result is achieved by enhancing IF with some additional control messages, aimed at the creation of cluster of nodes. Finally, the performance of the proposed protocols will be tested through numerical simulations in realistic vehicular environments, such as highways and urban roads, by using radio interfaces compliant with the IEEE 802.11p standard

Achieving Energy Efficiency on Networking Systems with Optimization Algorithms and Compressed Data Structures

To cope with the increasing quantity, capacity and energy consumption of transmission and routing equipment in the Internet, energy efficiency of communication networks has attracted more and more attention from researchers around the world. In this dissertation, we proposed three methodologies to achieve energy efficiency on networking devices: the NP-complete problems and heuristics, the compressed data structures, and the combination of the first two methods. We first consider the problem of achieving energy efficiency in Data Center Networks (DCN). We generalize the energy efficiency networking problem in data centers as optimal flow assignment problems, which is NP-complete, and then propose a heuristic called CARPO, a correlation-aware power optimization algorithm, that dynamically consolidate traffic flows onto a small set of links and switches in a DCN and then shut down unused network devices for power savings. We then achieve energy efficiency on Internet routers by using the compressive data structure. A novel data structure called the Probabilistic Bloom Filter (PBF), which extends the classical bloom filter into the probabilistic direction, so that it can effectively identify heavy hitters with a small memory foot print to reduce energy consumption of network measurement. To achieve energy efficiency on Wireless Sensor Networks (WSN), we developed one data collection protocol called EDAL, which stands for Energy-efficient Delay-aware Lifetime-balancing data collection. Based on the Open Vehicle Routing problem, EDAL exploits the topology requirements of Compressive Sensing (CS), then implement CS to save more energy on sensor nodes