Vertical handover based adaptions for multimedia applications in pervasive systems

This paper proposes an architecture for pervasive computing which utilizes context information to provide adaptations based on vertical handovers (handovers between heterogeneous networks) while supporting application Quality of Service (QoS). The future of mobile computing will see an increase in ubiquitous network connectivity which allows users to roam freely between heterogeneous networks. One of the requirements for pervasive computing is to adapt computing applications or their environment if current applications can no longer be provided with the requested QoS. One of possible adaptations is a vertical handover to a different network. Vertical handover operations include changing network interfaces on a single device or changes between different devices. Such handovers should be performed with minimal user distraction and minimal violation of communication QoS for user applications. The solution utilises context information regarding user devices, user location, application requirements, and network environment. The paper shows how vertical handover adaptations are incorporated into the whole infrastructure of a pervasive system

Causality and synchronisation in complex systems with applications to neuroscience

This thesis presents an investigation, of synchronisation and causality, motivated by problems in computational neuroscience. The thesis addresses both theoretical and practical signal processing issues regarding the estimation of interdependence from a set of multivariate data generated by a complex underlying dynamical system. This topic is driven by a series of problems in neuroscience, which represents the principal background motive behind the material in this work. The underlying system is the human brain and the generative process of the data is based on modern electromagnetic neuroimaging methods . In this thesis, the underlying functional of the brain mechanisms are derived from the recent mathematical formalism of dynamical systems in complex networks. This is justified principally on the grounds of the complex hierarchical and multiscale nature of the brain and it offers new methods of analysis to model its emergent phenomena. A fundamental approach to study the neural activity is to investigate the connectivity pattern developed by the brain’s complex network. Three types of connectivity are important to study: 1) anatomical connectivity refering to the physical links forming the topology of the brain network; 2) effective connectivity concerning with the way the neural elements communicate with each other using the brain’s anatomical structure, through phenomena of synchronisation and information transfer; 3) functional connectivity, presenting an epistemic concept which alludes to the interdependence between data measured from the brain network. The main contribution of this thesis is to present, apply and discuss novel algorithms of functional connectivities, which are designed to extract different specific aspects of interaction between the underlying generators of the data. Firstly, a univariate statistic is developed to allow for indirect assessment of synchronisation in the local network from a single time series. This approach is useful in inferring the coupling as in a local cortical area as observed by a single measurement electrode. Secondly, different existing methods of phase synchronisation are considered from the perspective of experimental data analysis and inference of coupling from observed data. These methods are designed to address the estimation of medium to long range connectivity and their differences are particularly relevant in the context of volume conduction, that is known to produce spurious detections of connectivity. Finally, an asymmetric temporal metric is introduced in order to detect the direction of the coupling between different regions of the brain. The method developed in this thesis is based on a machine learning extensions of the well known concept of Granger causality. The thesis discussion is developed alongside examples of synthetic and experimental real data. The synthetic data are simulations of complex dynamical systems with the intention to mimic the behaviour of simple cortical neural assemblies. They are helpful to test the techniques developed in this thesis. The real datasets are provided to illustrate the problem of brain connectivity in the case of important neurological disorders such as Epilepsy and Parkinson’s disease. The methods of functional connectivity in this thesis are applied to intracranial EEG recordings in order to extract features, which characterize underlying spatiotemporal dynamics before during and after an epileptic seizure and predict seizure location and onset prior to conventional electrographic signs. The methodology is also applied to a MEG dataset containing healthy, Parkinson’s and dementia subjects with the scope of distinguishing patterns of pathological from physiological connectivity.

Enterprise networking:multilayer switching and applications

Primarily targeted toward the network or MIS manager who wants to stay abreast of the latest networking technology, Enterprise Networking: Multilayer Switching and Applications offers up to date information relevant for the design of modern corporate networks and for the evaluation of new networking equipment. The book describes the architectures and standards of switching across the various protocol layers and will also address issues such as multicast quality of service, high-availability and network policies that are requirements of modern switched networks.

Exploitation of fibre characteristics in temperature sensing and radio-over-fibre applications

The development of sensing devices is one of the instrumentation fields that has grown rapidly in the last decade. Corresponding to the swift advance in the development of microelectronic sensors, optical fibre sensors are widely investigated because of their advantageous properties over the electronics sensors such as their wavelength multiplexing capability and high sensitivity to temperature, pressure, strain, vibration and acoustic emission. Moreover, optical fibre sensors are more attractive than the electronics sensors as they can perform distributed sensing, in terms of covering a reasonably large area using a single piece of fibre. Apart from being a responsive element in the sensing field, optical fibre possesses good assets in generating, distributing, processing and transmitting signals in the future broadband information network. These assets include wide bandwidth, high capacity and low loss that grant mobility and flexibility for wireless access systems. Among these core technologies, the fibre optic signal processing and transmission of optical and radio frequency signals have been the subjects of study in this thesis. Based on the intrinsic properties of single-mode optical fibre, this thesis aims to exploit the fibre characteristics such as thermal sensitivity, birefringence, dispersion and nonlinearity, in the applications of temperature sensing and radio-over-fibre systems. By exploiting the fibre thermal sensitivity, a fully distributed temperature sensing system consisting of an apodised chirped fibre Bragg grating has been implemented. The proposed system has proven to be efficient in characterising grating and providing the information of temperature variation, location and width of the heat source applied in the area under test.To exploit the fibre birefringence, a fibre delay line filter using a single high-birefringence optical fibre structure has been presented. The proposed filter can be reconfigured and programmed by adjusting the input azimuth of launched light, as well as the strength and direction of the applied coupling, to meet the requirements of signal processing for different purposes in microwave photonic and optical filtering applications. To exploit the fibre dispersion and nonlinearity, experimental investigations have been carried out to study their joint effect in high power double-sideband and single-sideband modulated links with the presence of fibre loss. The experimental results have been theoretically verified based on the in-house implementation of the split-step Fourier method applied to the generalised nonlinear Schrödinger equation. Further simulation study on the inter-modulation distortion in two-tone signal transmission has also been presented so as to show the effect of nonlinearity of one channel on the other. In addition to the experimental work, numerical simulations have also been carried out in all the proposed systems, to ensure that all the aspects concerned are comprehensively investigated.

Advanced optical fibre gratings and applications

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT This thesis describes a detailed study of advanced optical fibre sensors based on fibre Bragg grating (FBG), tilted fibre Bragg grating (TFBG) and long-period grating (LPG) and their applications in optical communications and sensing. The major contributions presented in this thesis are summarised below.The most important contribution from the research work presented in this thesis is the implementation of in-fibre grating based refractive index (RI) sensors, which could be the good candidates for optical biochemical sensing. Several fibre grating based RI sensors have been proposed and demonstrated by exploring novel grating structures and different fibre types, and employing efficient hydrofluoric acid etching technique to enhance the RI sensitivity. All the RI devices discussed in this thesis have been used to measure the concentration of sugar solution to simulate the chemical sensing. Efforts have also been made to overcome the RI-temperature cross-sensitivity for practical application. The demonstrated in-fibre grating based RI sensors could be further implemented as potential optical biosensors by applying bioactive coatings to realise high bio-sensitivity and bio-selectivity.Another major contribution of this thesis is the application of TFBGs. A prototype interrogation system by the use of TFBG with CCD-array was implemented to perform wavelength division multiplexing (WDM) interrogation around 800nm wavelength region with the advantages of compact size, fast detection speed and low-cost. As a high light, a novel in-fibre twist sensors utilising strong polarisation dependant coupling behaviour of an 81°-TFBG was presented to demonstrate the high torsion sensitivity and capability of direction recognition.