The learning dynamics of a universal approximator

The learning properties of a universal approximator, a normalized committee machine with adjustable biases, are studied for on-line back-propagation learning. Within a statistical mechanics framework, numerical studies show that this model has features which do not exist in previously studied two-layer network models without adjustable biases, e.g., attractive suboptimal symmetric phases even for realizable cases and noiseless data.

Natural gradient matrix momentum

Natural gradient learning is an efficient and principled method for improving on-line learning. In practical applications there will be an increased cost required in estimating and inverting the Fisher information matrix. We propose to use the matrix momentum algorithm in order to carry out efficient inversion and study the efficacy of a single step estimation of the Fisher information matrix. We analyse the proposed algorithm in a two-layer network, using a statistical mechanics framework which allows us to describe analytically the learning dynamics, and compare performance with true natural gradient learning and standard gradient descent.

Performance comparison of OFDM bandwidth request schemes in fixed IEEE 802.16 networks

IEEE 802.16 standard specifies two contention based bandwidth request schemes working with OFDM physical layer specification in point-to-multipoint (PMP) architecture, the mandatory one used in region-full and the optional one used in region-focused. This letter presents a unified analytical model to study the bandwidth efficiency and channel access delay performance of the two schemes. The impacts of access parameters, available bandwidth and subchannelization have been taken into account. The model is validated by simulations. The mandatory scheme is observed to perform closely to the optional one when subchannelization is active for both schemes.

Quality of transmission estimation in WDM and elastic optical networks accounting for space-spectrum dependencies

We develop a framework for estimating the quality of transmission (QoT) of a new lightpath before it is established, as well as for calculating the expected degradation it will cause to existing lightpaths. The framework correlates the QoT metrics of established lightpaths, which are readily available from coherent optical receivers that can be extended to serve as optical performance monitors. Past similar studies used only space (routing) information and thus neglected spectrum, while they focused on oldgeneration noncoherent networks. The proposed framework accounts for correlation in both the space and spectrum domains and can be applied to both fixed-grid wavelength division multiplexing (WDM) and elastic optical networks. It is based on a graph transformation that exposes and models the interference between spectrum-neighboring channels. Our results indicate that our QoT estimates are very close to the actual performance data, that is, to having perfect knowledge of the physical layer. The proposed estimation framework is shown to provide up to 4 × 10-2 lower pre-forward error correction bit error ratio (BER) compared to theworst-case interference scenario,which overestimates the BER. The higher accuracy can be harvested when lightpaths are provisioned with low margins; our results showed up to 47% reduction in required regenerators, a substantial savings in equipment cost.

Secure Wireless Key Establishment Using Retrodirective Array

In this paper a new method of establishing secret keys for wireless communications is proposed. A retrodirective array (RDA) that is configured to receive and re-transmit at different frequencies is utilized as a relay node. Specifically the analogue RDA is able to respond in ‘real-time’, reducing the required number of time slots for key establishment to two, compared with at least three in previous relay key generation schemes. More importantly, in the proposed architecture equivalent reciprocal wireless channels between legitimate keying nodes can be randomly updated within one channel coherence time period, leading to greatly increased key generation rates (KGRs) in slow fading environment. The secrecy performance of this RDA assisted key generation system is evaluated and it is shown that it outperforms previous relay key generation systems.

Spectral Signature Secured Retrodirective Array

A novel retrodirective array (RDA) architecture is proposed which utilises a special case spectral signature embedded within the data payload as pilot signals. With the help of a pair of phase-locked-loop (PLL) based phase conjugators (PCs) the RDA’s response to other unwanted and/or unfriendly interrogating signals can be disabled, leading to enhanced secrecy performance directly in the wireless physical layer. The effectiveness of the proposed RDA system is experimentally demonstrated.

Size effects on self-assembly and melting of silver-alkanethiolate on inert surfaces

Self-assembled materials produced in the reaction between alkanethiol and Ag are characterized and compared. It is revealed that the size of the Ag substrate has a significant role in the self-assembly process and determines the reaction products. Alkanethiol adsorbs on the surface of Ag continuous planar thin films and only forms self-assembled monolayers (SAMs), while the reaction between alkanethiol and Ag clusters on inert surfaces is more aggressive and generates a significantly larger amount of alkanethiolate. Two dissimilar products are yielded depending on the size of the clusters. Small Ag clusters are more likely to be converted into multilayer silver-alkanethiolate (AgSR, R = CnH2n+1) crystals, while larger Ag clusters form monolayer-protected clusters (MPCs). The AgSR crystals are initially small and can ripen into large lamellae during thermal annealing. The crystals have facets and flat terraces with extended area, and have a strong preferred orientation in parallel with the substrate surface. The MPCs move laterally upon annealing and reorganize into a single-layer network with their separation distance approximately equal to the length of an extended alkyl chain. AgSR lamellar crystals grown on inert surfaces provide an excellent platform to study the melting characteristics of crystalline lamellae of polymeric materials with the thickness in the nanometer scale. This system is also unique in that each crystal has integer number of layers – magic-number size (thickness). The size of the crystals is controlled by adjusting the amount of Ag and the annealing temperature. X-ray diffraction (XRD) and atomic force microscopy (AFM) are combined to accurately determine the size (number of layers) of the lamellar crystals. The melting characteristics are measured with nanocalorimetry and show discrete melting transitions which are attributed to the magic-number sizes of the lamellar crystals. The discrete melting temperatures are intrinsic properties of the crystals with particular sizes. Smaller lamellar crystals with less number of layers melt at lower temperatures. The melting point depression is inversely proportional to the total thickness of the lamellae – the product of the number of layers and the layer thickness.

NETCODE: an XOR-based warning dissemination scheme for vehicular wireless networks

The next generation of vehicles will be equipped with automated Accident Warning Systems (AWSs) capable of warning neighbouring vehicles about hazards that might lead to accidents. The key enabling technology for these systems is the Vehicular Ad-hoc Networks (VANET) but the dynamics of such networks make the crucial timely delivery of warning messages challenging. While most previously attempted implementations have used broadcast-based data dissemination schemes, these do not cope well as data traffic load or network density increases. This problem of sending warning messages in a timely manner is addressed by employing a network coding technique in this thesis. The proposed NETwork COded DissEmination (NETCODE) is a VANET-based AWS responsible for generating and sending warnings to the vehicles on the road. NETCODE offers an XOR-based data dissemination scheme that sends multiple warning in a single transmission and therefore, reduces the total number of transmissions required to send the same number of warnings that broadcast schemes send. Hence, it reduces contention and collisions in the network improving the delivery time of the warnings. The first part of this research (Chapters 3 and 4) asserts that in order to build a warning system, it is needful to ascertain the system requirements, information to be exchanged, and protocols best suited for communication between vehicles. Therefore, a study of these factors along with a review of existing proposals identifying their strength and weakness is carried out. Then an analysis of existing broadcast-based warning is conducted which concludes that although this is the most straightforward scheme, loading can result an effective collapse, resulting in unacceptably long transmission delays. The second part of this research (Chapter 5) proposes the NETCODE design, including the main contribution of this thesis, a pair of encoding and decoding algorithms that makes the use of an XOR-based technique to reduce transmission overheads and thus allows warnings to get delivered in time. The final part of this research (Chapters 6--8) evaluates the performance of the proposed scheme as to how it reduces the number of transmissions in the network in response to growing data traffic load and network density and investigates its capacity to detect potential accidents. The evaluations use a custom-built simulator to model real-world scenarios such as city areas, junctions, roundabouts, motorways and so on. The study shows that the reduction in the number of transmissions helps reduce competition in the network significantly and this allows vehicles to deliver warning messages more rapidly to their neighbours. It also examines the relative performance of NETCODE when handling both sudden event-driven and longer-term periodic messages in diverse scenarios under stress caused by increasing numbers of vehicles and transmissions per vehicle. This work confirms the thesis' primary contention that XOR-based network coding provides a potential solution on which a more efficient AWS data dissemination scheme can be built.

Analyzing downloaded data from road side units

En el contexto de las redes vehiculares, analizamos una aplicación de descarga de mapas, donde cada vehículo descarga datos de mapas relevantes según su posición. Entre las estrategias propuestas está la de utilizar las redes con infraestructura (I2V) además de las redes vehículo a vehículo (V2V). En este trabajo comparamos dos métodos de fragmentación de archivos, para el segmento I2V; los métodos son Random Sort Strategy (RSS) y Network Coding (NC). Encontramos que: cuando se utiliza NC la distribución de los diferentes fragmentos recibidos es independiente del tamaño del archivo. Cuando se utiliza RSS, la media y la desviación estándar dependen del tamaño del archivo. Estos resultados serán utilizados para el análisis del segmento V2V de la red.

Rank metric convolutional codes

In this contribution, we propose a first general definition of rank-metric convolutional codes for multi-shot network coding. To this aim, we introduce a suitable concept of distance and we establish a generalized Singleton bound for this class of codes.

Quantifying the Resilience of an Urban Traffic-Electric Power Coupled System

Transportation system resilience has been the subject of several recent studies. To assess the resilience of a transportation network, however, it is essential to model its interactions with and reliance on other lifelines. In this work, a bi-level, mixed-integer, stochastic program is presented for quantifying the resilience of a coupled traffic-power network under a host of potential natural or anthropogenic hazard-impact scenarios. A two-layer network representation is employed that includes details of both systems. Interdependencies between the urban traffic and electric power distribution systems are captured through linking variables and logical constraints. The modeling approach was applied on a case study developed on a portion of the signalized traffic-power distribution system in southern Minneapolis. The results of the case study show the importance of explicitly considering interdependencies between critical infrastructures in transportation resilience estimation. The results also provide insights on lifeline performance from an alternative power perspective.

Wireless solutions for the industrial internet of things

The fourth industrial revolution is paving the way for Industrial Internet of Things applications where industrial assets (e.g., robotic arms, valves, pistons) are equipped with a large number of wireless devices (i.e., microcontroller boards that embed sensors and actuators) to enable a plethora of new applications, such as analytics, diagnostics, monitoring, as well as supervisory, and safety control use-cases. Nevertheless, current wireless technologies, such as Wi-Fi, Bluetooth, and even private 5G networks, cannot fulfill all the requirements set up by the Industry 4.0 paradigm, thus opening up new 6G-oriented research trends, such as the use of THz frequencies. In light of the above, this thesis provides (i) a broad overview of the main use-cases, requirements, and key enabling wireless technologies foreseen by the fourth industrial revolution, and (ii) proposes innovative contributions, both theoretical and empirical, to enhance the performance of current and future wireless technologies at different levels of the protocol stack. In particular, at the physical layer, signal processing techniques are being exploited to analyze two multiplexing schemes, namely Affine Frequency Division Multiplexing and Orthogonal Chirp Division Multiplexing, which seem promising for high-frequency wireless communications. At the medium access layer, three protocols for intra-machine communications are proposed, where one is based on LoRa at 2.4 GHz and the others work in the THz band. Different scheduling algorithms for private industrial 5G networks are compared, and two main proposals are described, i.e., a decentralized scheme that leverages machine learning techniques to better address aperiodic traffic patterns, and a centralized contention-based design that serves a federated learning industrial application. Results are provided in terms of numerical evaluations, simulation results, and real-world experiments. Several improvements over the state-of-the-art were obtained, and the description of up-and-running testbeds demonstrates the feasibility of some of the theoretical concepts when considering a real industry plant.

Joint physical-MAC layer design of the broadcast channel protocol in adhoc networks

Broadcast transmission mode in ad hoc networks is critical to manage multihop routing or providing medium accesscontrol (MAC)-layer fairness. In this paper, it is shown that ahigher capacity to exchange information among neighbors may beobtained through a physical-MAC cross-layer design of the broadcastprotocol exploiting signal separation principles. Coherentdetection and separation of contending nodes is possible throughtraining sequences which are selected at random from a reducedset. Guidelines for the design of this set are derived for a lowimpact on the network performance and the receiver complexity.

jxSensor: a sensor network integration layer for JXTA

Nowadays, Wireless Sensor Networks (WSN) arealready a very important data source to obtain data about the environment. Thus, they are key to the creation of Cyber-Physical Systems (CPS). Given the popularity of P2P middlewares as ameans to efficiently process information and distribute services, being able to integrate them to WSN¿s is an interesting proposal. JXTA is a widely used P2P middleware that allows peers to easily exchange information, heavily relying on its main architectural highlight, the capability to organize peers with common interests into peer groups. However, right now, approaches to integrate WSNs to a JXTA network seldom take advantage of peer groups. For this reason, in this paper we present jxSensor, an integrationlayer for sensor motes which facilitates the deployment of CPS¿s under this architecture. This integration has been done taking into account JXTA¿s idiosyncrasies and proposing novel ideas,such as the Virtual Peer, a group of sensors that acts as a single entity within the peer group context.

An overview on the urban boundary-layer atmosphere network in Helsinki

The Helsinki Urban Boundary-Layer Atmosphere Network (UrBAN: http://urban.fmi.fi) is a dedicated research-grade observational network where the physical processes in the atmosphere above the city are studied. Helsinki UrBAN is the most poleward intensive urban research observation network in the world and thus will allow studying some unique features such as strong seasonality. The network's key purpose is for the understanding of the physical processes in the urban boundary layer and associated fluxes of heat, momentum, moisture, and other gases. A further purpose is to secure a research-grade database, which can be used internationally to validate and develop numerical models of air quality and weather prediction. Scintillometers, a scanning Doppler lidar, ceilometers, a sodar, eddy-covariance stations, and radiometers are used. This equipment is supplemented by auxiliary measurements, which were primarily set up for general weather and/or air-quality mandatory purposes, such as vertical soundings and the operational Doppler radar network. Examples are presented as a testimony to the potential of the network for urban studies, such as (i) evidence of a stable boundary layer possibly coupled to an urban surface, (ii) the comparison of scintillometer data with sonic anemometry above an urban surface, (iii) the application of scanning lidar over a city, and (iv) combination of sodar and lidar to give a fuller range of sampling heights for boundary layer profiling.