Schedulability, Response Time Analysis and New Models of P-FRP Systems

Functional Reactive Programming (FRP) is a declarative approach for modeling and building reactive systems. FRP has been shown to be an expressive formalism for building applications of computer graphics, computer vision, robotics, etc. Priority-based FRP (P-FRP) is a formalism that allows preemption of executing programs and guarantees real-time response. Since functional programs cannot maintain state and mutable data, changes made by programs that are preempted have to be rolled back. Hence in P-FRP, a higher priority task can preempt the execution of a lower priority task, but the preempted lower priority task will have to restart after the higher priority task has completed execution. This execution paradigm is called Abort-and-Restart (AR). Current real-time research is focused on preemptive of non-preemptive models of execution and several state-of-the-art methods have been developed to analyze the real-time guarantees of these models. Unfortunately, due to its transactional nature where preempted tasks are aborted and have to restart, the execution semantics of P-FRP does not fit into the standard definitions of preemptive or non-preemptive execution, and the research on the standard preemptive and non-preemptive may not applicable for the P-FRP AR model. Out of many research areas that P-FRP may demands, we focus on task scheduling which includes task and system modeling, priority assignment, schedulability analysis, response time analysis, improved P-FRP AR models, algorithms and corresponding software. In this work, we review existing results on P-FRP task scheduling and then present our research contributions: (1) a tighter feasibility test interval regarding the task release offsets as well as a linked list based algorithm and implementation for scheduling simulation; (2) P-FRP with software transactional memory-lazy conflict detection (STM-LCD); (3) a non-work-conserving scheduling model called Deferred Start; (4) a multi-mode P-FRP task model; (5) SimSo-PFRP, the P-FRP extension of SimSo - a SimPy-based, highly extensible and user friendly task generator and task scheduling simulator.Computer Science, Department o

Schedulability Analysis for the Abort-and-Restart Model

In real-time systems, a schedulable task-set guarantees that all tasks complete before their deadlines. In functional programming, atomic execution provides the correctness of the program. Priority-based functional reactive programming (P-FRP) allows the usage of functional programming in the real-time system environment. The abort-and-restart (AR) is a scheme to implement P-FRP but an appropriate scheduling approach does not exist at the moment. Hence, efficient analysis is needed for the AR model. In this thesis, the schedulability analysis for the AR model is introduced and it shows that finding the critical instant for the AR model with periodic and sporadic tasks is intractable, and a new formulation is derived. Afterwards, a new priority assignment scheme is developed that has the performance close to the exhaustive search method, which is intractable for large systems. The technique of deferred preemption is employed and a new model, deferred abort (DA), provides better schedulability and dominates the non-preemptive model. Lastly, a tighter analysis is introduced and the technique of the multi-set approach from the analysis of cache related preemption delay is employed to introduce a new approach, multi-bag. The multi-bag approach can apply to both the AR model and the DA model. In the experiments, the schedulability of the AR model is improved at each stage of the research in this thesis

Multiscale Machine Learning and Numerical Investigation of Ageing in Infrastructures

Infrastructure is a critical component of a country’s economic growth. Interaction with extreme service environments can adversely affect the long-term performance of infrastructure and accelerate ageing. This research focuses on using machine learning to improve the efficiency of analysing the multiscale ageing impact on infrastructure. First, a data-driven campaign is developed to analyse the condition of an ageing infrastructure. A machine learning-based framework is proposed to predict the state of various assets across a railway system. The ageing of the bond in fibre-reinforced polymer (FRP)-strengthened concrete elements is investigated using machine learning. Different machine learning models are developed to characterise the long-term performance of the bond. The environmental ageing of composite materials is investigated by a micromechanics-based machine learning model. A mathematical framework is developed to automatically generate microstructures. The microstructures are analysed by the finite element (FE) method. The generated data is used to develop a machine learning model to study the degradation of the transverse performance of composites under humid conditions. Finally, a multiscale FE and machine learning framework is developed to expand the understanding of composite material ageing. A moisture diffusion analysis is performed to simulate the water uptake of composites under water immersion conditions. The results are downscaled to obtain micromodel stress fields. Numerical homogenisation is used to obtain the composite transverse behaviour. A machine learning model is developed based on the multiscale simulation results to model the ageing process of composites under water immersion. The frameworks developed in this thesis demonstrate how machine learning improves the analysis of ageing across multiple scales of infrastructure. The resulting understanding can help develop more efficient strategies for the rehabilitation of ageing infrastructure

Constructing fail-controlled nodes for distributed systems: a software approach

PhD ThesisDesigning and implementing distributed systems which continue to provide specified services in the presence of processing site and communication failures is a difficult task. To facilitate their development, distributed systems have been built assuming that their underlying hardware components are Jail-controlled, i.e. present a well defined failure mode. However, if conventional hardware cannot provide the assumed failure mode, there is a need to build processing sites or nodes, and communication infra-structure that present the fail-controlled behaviour assumed. Coupling a number of redundant processors within a replicated node is a well known way of constructing fail-controlled nodes. Computation is replicated and executed simultaneously at each processor, and by employing suitable validation techniques to the outputs generated by processors (e.g. majority voting, comparison), outputs from faulty processors can be prevented from appearing at the application level. One way of constructing replicated nodes is by introducing hardwired mechanisms to couple replicated processors with specialised validation hardware circuits. Processors are tightly synchronised at the clock cycle level, and have their outputs validated by a reliable validation hardware. Another approach is to use software mechanisms to perform synchronisation of processors and validation of the outputs. The main advantage of hardware based nodes is the minimum performance overhead incurred. However, the introduction of special circuits may increase the complexity of the design tremendously. Further, every new microprocessor architecture requires considerable redesign overhead. Software based nodes do not present these problems, on the other hand, they introduce much bigger performance overheads to the system. In this thesis we investigate alternative ways of constructing efficient fail-controlled, software based replicated nodes. In particular, we present much more efficient order protocols, which are necessary for the implementation of these nodes. Our protocols, unlike others published to date, do not require processors' physical clocks to be explicitly synchronised. The main contribution of this thesis is the precise definition of the semantics of a software based Jail-silent node, along with its efficient design, implementation and performance evaluation.The Brazilian National Research Council (CNPq/Brasil)

Some aspects of traffic control and performance evaluation of ATM networks

The emerging high-speed Asynchronous Transfer Mode (ATM) networks are expected to integrate through statistical multiplexing large numbers of traffic sources having a broad range of statistical characteristics and different Quality of Service (QOS) requirements. To achieve high utilisation of network resources while maintaining the QOS, efficient traffic management strategies have to be developed. This thesis considers the problem of traffic control for ATM networks. The thesis studies the application of neural networks to various ATM traffic control issues such as feedback congestion control, traffic characterization, bandwidth estimation, and Call Admission Control (CAC). A novel adaptive congestion control approach based on a neural network that uses reinforcement learning is developed. It is shown that the neural controller is very effective in providing general QOS control. A Finite Impulse Response (FIR) neural network is proposed to adaptively predict the traffic arrival process by learning the relationship between the past and future traffic variations. On the basis of this prediction, a feedback flow control scheme at input access nodes of the network is presented. Simulation results demonstrate significant performance improvement over conventional control mechanisms. In addition, an accurate yet computationally efficient approach to effective bandwidth estimation for multiplexed connections is investigated. In this method, a feed forward neural network is employed to model the nonlinear relationship between the effective bandwidth and the traffic situations and a QOS measure. Applications of this approach to admission control, bandwidth allocation and dynamic routing are also discussed. A detailed investigation has indicated that CAC schemes based on effective bandwidth approximation can be very conservative and prevent optimal use of network resources. A modified effective bandwidth CAC approach is therefore proposed to overcome the drawback of conventional methods. Considering statistical multiplexing between traffic sources, we directly calculate the effective bandwidth of the aggregate traffic which is modelled by a two-state Markov modulated Poisson process via matching four important statistics. We use the theory of large deviations to provide a unified description of effective bandwidths for various traffic sources and the associated ATM multiplexer queueing performance approximations, illustrating their strengths and limitations. In addition, a more accurate estimation method for ATM QOS parameters based on the Bahadur-Rao theorem is proposed, which is a refinement of the original effective bandwidth approximation and can lead to higher link utilisation

Behaviour of R.C. beams upgraded with externally bonded steel or FRP plates

The structural behaviour of simply supported reinforced concrete (R.C.) beams strengthened in flexure by externally bonded steel or fibre reinforced plastic (FRP) plates has been investigated. A novel theoretical model coupled with simple (hence, practical) procedure(s) for designing such beams against premature plate peeling failure has been developed. The theoretical model and the design procedures have been validated by an extensive number (169) of mainly large-scale test data (using steel or FRP plates) from other sources. The effects of variations in the magnitude of Young's modulus for FRP plates on the potential changes in the flexural ultimate load of R. C. beams with externally bonded FRP plates, in the absence and/or presence of plate peeling, have been investigated in some detail with the theoretical predictions of various failure loads and associated modes of failure supported by an extensive number of test results from other sources. Moreover, brief theoretical parametric studies for other first order composite beam design parameters have also been carried out in order to clarify the effects of variations in such parameters on the predicted modes of failure. It has been shown (both, theoretically and by using large scale experimental data) that the load bearing capacity for a plated beam could (under certain circumstances) be significantly lower than even that for the corresponding unplated beam with the mode of failure being of an undesirable brittle nature. Such brittle failures can obviously have serious implications in practice, where this method has been used extensively for upgrading both bridges and buildings in a number of countries, with the design calculations very often not having properly accounted for the possible occurrence of premature plate peeling phenomenon, especially when FRP plates have been used. Further work in this area included a quantitative theoretical insight into the effect of pre-cracking of the beams (under service conditions) on the ultimate plate peeling load. A critical quantitative examination of a number of previously available theoretical models, as proposed by others, has also been carried out, and some of these models for predicting the plate peeling failure of R. C. beams have been shown to suffer from rather serious shortcomings

Performance modelling and the representation of large scale distributed system functions

This thesis presents a resource based approach to model generation for performance characterization and correctness checking of large scale telecommunications networks. A notion called the timed automaton is proposed and then developed to encapsulate behaviours of networking equipment, system control policies and non-deterministic user behaviours. The states of pooled network resources and the behaviours of resource consumers are represented as continually varying geometric patterns; these patterns form part of the data operated upon by the timed automata. Such a representation technique allows for great flexibility regarding the level of abstraction that can be chosen in the modelling of telecommunications systems. None the less, the notion of system functions is proposed to serve as a constraining framework for specifying bounded behaviours and features of telecommunications systems. Operational concepts are developed for the timed automata; these concepts are based on limit preserving relations. Relations over system states represent the evolution of system properties observable at various locations within the network under study. The declarative nature of such permutative state relations provides a direct framework for generating highly expressive models suitable for carrying out optimization experiments. The usefulness of the developed procedure is demonstrated by tackling a large scale case study, in particular the problem of congestion avoidance in networks; it is shown that there can be global coupling among local behaviours within a telecommunications network. The uncovering of such a phenomenon through a function oriented simulation is a contribution to the area of network modelling. The direct and faithful way of deriving performance metrics for loss in networks from resource utilization patterns is also a new contribution to the work area