A real-time asymmetric multiprocessor-reconfigurable system-on-chip architecture

We propose an asymmetric multi-processor SoC architecture, featuring a master CPU running uClinux, and multiple loosely-coupled slave CPUs running real-time threads assigned by the master CPU. Real-time SoC architectures often demand a compromise between a generic platform for different applications, and application-specific customizations to achieve performance requirements. Our proposed architecture offers a generic platform running a conventional embedded operating system providing a traditional software-oriented development approach, while multiple slave CPUs act as a dedicated independent real-time threads execution unit running in parallel of master CPU to achieve performance requirements. In this paper, the architecture is described, including the application / threading development environment. The performance of the architecture with several standard benchmark routines is also analysed.

Efficient Data Management with Applications to IoT

The Internet of Things (IoT) consists of a worldwide “network of networks,” composed by billions of interconnected heterogeneous devices denoted as things or “Smart Objects” (SOs). Significant research efforts have been dedicated to port the experience gained in the design of the Internet to the IoT, with the goal of maximizing interoperability, using the Internet Protocol (IP) and designing specific protocols like the Constrained Application Protocol (CoAP), which have been widely accepted as drivers for the effective evolution of the IoT. This first wave of standardization can be considered successfully concluded and we can assume that communication with and between SOs is no longer an issue. At this time, to favor the widespread adoption of the IoT, it is crucial to provide mechanisms that facilitate IoT data management and the development of services enabling a real interaction with things. Several reference IoT scenarios have real-time or predictable latency requirements, dealing with billions of device collecting and sending an enormous quantity of data. These features create a new need for architectures specifically designed to handle this scenario, hear denoted as “Big Stream”. In this thesis a new Big Stream Listener-based Graph architecture is proposed. Another important step, is to build more applications around the Web model, bringing about the Web of Things (WoT). As several IoT testbeds have been focused on evaluating lower-layer communication aspects, this thesis proposes a new WoT Testbed aiming at allowing developers to work with a high level of abstraction, without worrying about low-level details. Finally, an innovative SOs-driven User Interface (UI) generation paradigm for mobile applications in heterogeneous IoT networks is proposed, to simplify interactions between users and things.

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.

The challenge of real-time automatic mapping for environmental monitoring network management

The automatic interpolation of environmental monitoring network data such as air quality or radiation levels in real-time setting poses a number of practical and theoretical questions. Among the problems found are (i) dealing and communicating uncertainty of predictions, (ii) automatic (hyper)parameter estimation, (iii) monitoring network heterogeneity, (iv) dealing with outlying extremes, and (v) quality control. In this paper we discuss these issues, in light of the spatial interpolation comparison exercise held in 2004.

Pragmatic approach to the development of robust real-time protocols

This research is concerned with the development of distributed real-time systems, in which software is used for the control of concurrent physical processes. These distributed control systems are required to periodically coordinate the operation of several autonomous physical processes, with the property of an atomic action. The implementation of this coordination must be fault-tolerant if the integrity of the system is to be maintained in the presence of processor or communication failures. Commit protocols have been widely used to provide this type of atomicity and ensure consistency in distributed computer systems. The objective of this research is the development of a class of robust commit protocols, applicable to the coordination of distributed real-time control systems. Extended forms of the standard two phase commit protocol, that provides fault-tolerant and real-time behaviour, were developed. Petri nets are used for the design of the distributed controllers, and to embed the commit protocol models within these controller designs. This composition of controller and protocol model allows the analysis of the complete system in a unified manner. A common problem for Petri net based techniques is that of state space explosion, a modular approach to both the design and analysis would help cope with this problem. Although extensions to Petri nets that allow module construction exist, generally the modularisation is restricted to the specification, and analysis must be performed on the (flat) detailed net. The Petri net designs for the type of distributed systems considered in this research are both large and complex. The top down, bottom up and hybrid synthesis techniques that are used to model large systems in Petri nets are considered. A hybrid approach to Petri net design for a restricted class of communicating processes is developed. Designs produced using this hybrid approach are modular and allow re-use of verified modules. In order to use this form of modular analysis, it is necessary to project an equivalent but reduced behaviour on the modules used. These projections conceal events local to modules that are not essential for the purpose of analysis. To generate the external behaviour, each firing sequence of the subnet is replaced by an atomic transition internal to the module, and the firing of these transitions transforms the input and output markings of the module. Thus local events are concealed through the projection of the external behaviour of modules. This hybrid design approach preserves properties of interest, such as boundedness and liveness, while the systematic concealment of local events allows the management of state space. The approach presented in this research is particularly suited to distributed systems, as the underlying communication model is used as the basis for the interconnection of modules in the design procedure. This hybrid approach is applied to Petri net based design and analysis of distributed controllers for two industrial applications that incorporate the robust, real-time commit protocols developed. Temporal Petri nets, which combine Petri nets and temporal logic, are used to capture and verify causal and temporal aspects of the designs in a unified manner.

The design of robust protocols for distributed real-time systems

Modern distributed control systems comprise of a set of processors which are interconnected using a suitable communication network. For use in real-time control environments, such systems must be deterministic and generate specified responses within critical timing constraints. Also, they should be sufficiently robust to survive predictable events such as communication or processor faults. This thesis considers the problem of coordinating and synchronizing a distributed real-time control system under normal and abnormal conditions. Distributed control systems need to periodically coordinate the actions of several autonomous sites. Often the type of coordination required is the all or nothing property of an atomic action. Atomic commit protocols have been used to achieve this atomicity in distributed database systems which are not subject to deadlines. This thesis addresses the problem of applying time constraints to atomic commit protocols so that decisions can be made within a deadline. A modified protocol is proposed which is suitable for real-time applications. The thesis also addresses the problem of ensuring that atomicity is provided even if processor or communication failures occur. Previous work has considered the design of atomic commit protocols for use in non time critical distributed database systems. However, in a distributed real-time control system a fault must not allow stringent timing constraints to be violated. This thesis proposes commit protocols using synchronous communications which can be made resilient to a single processor or communication failure and still satisfy deadlines. Previous formal models used to design commit protocols have had adequate state coverability but have omitted timing properties. They also assumed that sites communicated asynchronously and omitted the communications from the model. Timed Petri nets are used in this thesis to specify and design the proposed protocols which are analysed for consistency and timeliness. Also the communication system is mcxielled within the Petri net specifications so that communication failures can be included in the analysis. Analysis of the Timed Petri net and the associated reachability tree is used to show the proposed protocols always terminate consistently and satisfy timing constraints. Finally the applications of this work are described. Two different types of applications are considered, real-time databases and real-time control systems. It is shown that it may be advantageous to use synchronous communications in distributed database systems, especially if predictable response times are required. Emphasis is given to the application of the developed commit protocols to real-time control systems. Using the same analysis techniques as those used for the design of the protocols it can be shown that the overall system performs as expected both functionally and temporally.

Accuracy and applications of group MEG studies using cortical source locations estimated from participants' scalp surfaces

We contend that powerful group studies can be conducted using magnetoencephalography (MEG), which can provide useful insights into the approximate distribution of the neural activity detected with MEG without requiring magnetic resonance imaging (MRI) for each participant. Instead, a participant's MRI is approximated with one chosen as a best match on the basis of the scalp surface from a database of available MRIs. Because large inter-individual variability in sulcal and gyral patterns is an inherent source of blurring in studies using grouped functional activity, the additional error introduced by this approximation procedure has little effect on the group results, and offers a sufficiently close approximation to that of the participants to yield a good indication of the true distribution of the grouped neural activity. T1-weighted MRIs of 28 adults were acquired in a variety of MR systems. An artificial functional image was prepared for each person in which eight 5 × 5 × 5 mm regions of brain activation were simulated. Spatial normalisation was applied to each image using transformations calculated using SPM99 with (1) the participant's actual MRI, and (2) the best matched MRI substituted from those of the other 27 participants. The distribution of distances between the locations of points using real and substituted MRIs had a modal value of 6 mm with 90% of cases falling below 12.5 mm. The effects of this -approach on real grouped SAM source imaging of MEG data in a verbal fluency task are also shown. The distribution of MEG activity in the estimated average response is very similar to that produced when using the real MRIs. © 2003 Wiley-Liss, Inc.

Automatic processing, quality assurance and serving of real-time weather data over lightweight protocols

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

A systematic approach to establish fundamental principles of computer applications packages design

This work attempts to create a systemic design framework for man-machine interfaces which is self consistent, compatible with other concepts, and applicable to real situations. This is tackled by examining the current architecture of computer applications packages. The treatment in the main is philosophical and theoretical and analyses the origins, assumptions and current practice of the design of applications packages. It proposes that the present form of packages is fundamentally contradictory to the notion of packaging itself. This is because as an indivisible ready-to-implement solution, current package architecture displays the following major disadvantages. First, it creates problems as a result of user-package interactions, in which the designer tries to mould all potential individual users, no matter how diverse they are, into one model. This is worsened by the minute provision, if any, of important properties such as flexibility, independence and impartiality. Second, it displays rigid structure that reduces the variety and/or multi-use of the component parts of such a package. Third, it dictates specific hardware and software configurations which probably results in reducing the number of degrees of freedom of its user. Fourth, it increases the dependence of its user upon its supplier through inadequate documentation and understanding of the package. Fifth, it tends to cause a degeneration of the expertise of design of the data processing practitioners. In view of this understanding an alternative methodological design framework which is both consistent with systems approach and the role of a package in its likely context is proposed. The proposition is based upon an extension of the identified concept of the hierarchy of holons* which facilitates the examination of the complex relationships of a package with its two principal environments. First, the user characteristics and his decision making practice and procedures; implying an examination of the user's M.I.S. network. Second, the software environment and its influence upon a package regarding support, control and operation of the package. The framework is built gradually as discussion advances around the central theme of a compatible M.I.S., software and model design. This leads to the formation of the alternative package architecture that is based upon the design of a number of independent, self-contained small parts. Such is believed to constitute the nucleus around which not only packages can be more effectively designed, but is also applicable to many man-machine systems design.

Novel hardwired distributive tactile sensing system for medical applications

This thesis described the research carried out on the development of a novel hardwired tactile sensing system tailored for the application of a next generation of surgical robotic and clinical devices, namely a steerable endoscope with tactile feedback, and a surface plate for patient posture and balance. Two case studies are examined. The first is a one-dimensional sensor for the steerable endoscope retrieving shape and ‘touch’ information. The second is a two-dimensional surface which interprets the three-dimensional motion of a contacting moving load. This research can be used to retrieve information from a distributive tactile sensing surface of a different configuration, and can interpret dynamic and static disturbances. This novel approach to sensing has the potential to discriminate contact and palpation in minimal invasive surgery (MIS) tools, and posture and balance in patients. The hardwired technology uses an embedded system based on Field Programmable Gate Arrays (FPGA) as the platform to perform the sensory signal processing part in real time. High speed robust operation is an advantage from this system leading to versatile application involving dynamic real time interpretation as described in this research. In this research the sensory signal processing uses neural networks to derive information from input pattern from the contacting surface. Three neural network architectures namely single, multiple and cascaded were introduced in an attempt to find the optimum solution for discrimination of the contacting outputs. These architectures were modelled and implemented into the FPGA. With the recent introduction of modern digital design flows and synthesis tools that essentially take a high-level sensory processing behaviour specification for a design, fast prototyping of the neural network function can be achieved easily. This thesis outlines the challenge of the implementations and verifications of the performances.

An intelligent approach for deploying applications in WSN's

Wireless sensor networks have been identified as one of the key technologies for the 21st century. They consist of tiny devices with limited processing and power capabilities, called motes that can be deployed in large numbers of useful sensing capabilities. Even though, they are flexible and easy to deploy, there are a number of considerations when it comes to their fault tolerance, conserving energy and re-programmability that need to be addressed before we draw any substantial conclusions about the effectiveness of this technology. In order to overcome their limitations, we propose a middleware solution. The proposed scheme is composed based on two main methods. The first method involves the creation of a flexible communication protocol based on technologies such as Mobile Code/Agents and Linda-like tuple spaces. In this way, every node of the wireless sensor network will produce and process data based on what is the best for it but also for the group that it belongs too. The second method incorporates the above protocol in a middleware that will aim to bridge the gap between the application layer and low level constructs such as the physical layer of the wireless sensor network. A fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort towards the deployed applications running in an energy efficient manner inside the network. The proposed scheme is evaluated through a number of trials aiming to test its merits under real time conditions and to identify its effectiveness against other similar approaches. Finally, parameters which determine the characteristics of the proposed scheme are also examined.

Automatic processing, quality assurance and serving of real-time weather data

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

In-Motes EYE:a real time application for automobiles in wireless sensor networks

Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware solution, In-Motes. In-Motes stands as a fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort the deployed applications to run in an energy efficient manner inside the network. The proposed scheme is evaluated through the In-Motes EYE application, aiming to test its merits under real time conditions. In-Motes EYE application which is an agent based real time In-Motes application developed for sensing acceleration variations in an environment. The application was tested in a prototype area, road alike, for a period of four months.

UV-inscription, polarization-dependant loss characteristics and applications of 45° tilted fiber gratings

We have UV-inscribed and theoretically and experimentally analyzed fiber gratings with the structure tilted at 45° and implemented this type of devices as an in-fiber polarizer. A systematic investigation has been carried out on the characterization of 45° tilted fiber gratings (45° TFGs) in terms of the polarization-dependant loss (PDL) and thermal response. The detailed theoretical modeling has revealed a linear correlation between the grating length and the PDL, which has been proved by the experimental results. For the first time, we have examined the UV beam diffraction from a tilted phase mask and designed the UV-inscription system to suit the 45° TFG fabrication. Experimentally, a 24 mm long 45° TFG UV-inscribed in standard telecom single-mode fiber exhibited around 25 dB PDL at 1530 nm and an over ~300 nm bandwidth of PDL spectrum. By the concatenation method, a 44 mm long grating showed a PDL as high as 40 dB that is close to the high polarization extinction ratio of commercial products. Moreover, we have revealed that the PDL of 45° TFGs has low thermal influence, which is desirable for real application devices. Finally, we experimentally demonstrated an all-fiber twist sensor system based on a 45° and an 81° TFG.

Practical methods of tracking of nonstationary time series applied to real-world data

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.