Exploring resource/performance trade-offs for streaming applications on embedded multiprocessors

Embedded system design is challenged by the gap between the ever-increasing customer demands and the limited resource budgets. The tough competition demands ever-shortening time-to-market and product lifecycles. To solve or, at least to alleviate, the aforementioned issues, designers and manufacturers need model-based quantitative analysis techniques for early design-space exploration to study trade-offs of different implementation candidates. Moreover, modern embedded applications, especially the streaming applications addressed in this thesis, face more and more dynamic input contents, and the platforms that they are running on are more flexible and allow runtime configuration. Quantitative analysis techniques for embedded system design have to be able to handle such dynamic adaptable systems. This thesis has the following contributions: - A resource-aware extension to the Synchronous Dataflow (SDF) model of computation. - Trade-off analysis techniques, both in the time-domain and in the iterationdomain (i.e., on an SDF iteration basis), with support for resource sharing. - Bottleneck-driven design-space exploration techniques for resource-aware SDF. - A game-theoretic approach to controller synthesis, guaranteeing performance under dynamic input. As a first contribution, we propose a new model, as an extension of static synchronous dataflow graphs (SDF) that allows the explicit modeling of resources with consistency checking. The model is called resource-aware SDF (RASDF). The extension enables us to investigate resource sharing and to explore different scheduling options (ways to allocate the resources to the different tasks) using state-space exploration techniques. Consistent SDF and RASDF graphs have the property that an execution occurs in so-called iterations. An iteration typically corresponds to the processing of a meaningful piece of data, and it returns the graph to its initial state. On multiprocessor platforms, iterations may be executed in a pipelined fashion, which makes performance analysis challenging. As the second contribution, this thesis develops trade-off analysis techniques for RASDF, both in the time-domain and in the iteration-domain (i.e., on an SDF iteration basis), to dimension resources on platforms. The time-domain analysis allows interleaving of different iterations, but the size of the explored state space grows quickly. The iteration-based technique trades the potential of interleaving of iterations for a compact size of the iteration state space. An efficient bottleneck-driven designspace exploration technique for streaming applications, the third main contribution in this thesis, is derived from analysis of the critical cycle of the state space, to reveal bottleneck resources that are limiting the throughput. All techniques are based on state-based exploration. They enable system designers to tailor their platform to the required applications, based on their own specific performance requirements. Pruning techniques for efficient exploration of the state space have been developed. Pareto dominance in terms of performance and resource usage is used for exact pruning, and approximation techniques are used for heuristic pruning. Finally, the thesis investigates dynamic scheduling techniques to respond to dynamic changes in input streams. The fourth contribution in this thesis is a game-theoretic approach to tackle controller synthesis to select the appropriate schedules in response to dynamic inputs from the environment. The approach transforms the explored iteration state space of a scenario- and resource-aware SDF (SARA SDF) graph to a bipartite game graph, and maps the controller synthesis problem to the problem of finding a winning positional strategy in a classical mean payoff game. A winning strategy of the game can be used to synthesize the controller of schedules for the system that is guaranteed to satisfy the throughput requirement given by the designer

A cross-modal investigation into the relationships between bistable perception and a global temporal mechanism

When the two eyes are presented with sufficiently different images, Binocular Rivalry (BR) occurs. BR is a form of bistable perception involving stochastic alternations in awareness between distinct images shown to each eye. It has been suggested that the dynamics of BR are due to the activity of a central temporal process and are linked to involuntary mechanisms of selective attention (aka exogenous attention). To test these ideas, stimuli designed to evoke exogenous attention and central temporal processes were employed during BR observation. These stimuli included auditory and visual looming motion and streams of transient events of varied temporal rate and pattern. Although these stimuli exerted a strong impact over some aspects of BR, they were unable to override its characteristic stochastic pattern of alternations completely. It is concluded that BR is subject to distributed influences, but ultimately, is achieved in neural processing areas specific to the binocular conflict

Game-theoretic models for mergers and acquisitions

This thesis examines the corporate merger process as a bargaining game, under the assumption that the two companies are essentially in conflict over the single issue of the price to be offered by the acquirer to the target. The first part of the thesis deals with the construction and testing of analytical game-theoretic models to explain the proportion of the synergy gains accruing to the target company under different assumptions about the players' a priori knowledge. Assuming full certainty amongst the players about the pre- and post-merger values of the companies, the distribution of gains between target and acquiring companies that would be consistent with the Nash-Kalai axioms is determined in principle. The resulting model depends on the players' utility functions, and is parameterised by the relative bargaining strength of the players and their risk aversion coefficients. An operational version of the model is fitted to empirical data from a set of 24 recent mergers of companies quoted on the Johannesburg Stock Exchange. The model is shown to have good predictive power within this data set. Under the more realistic assumption of shared uncertainty amongst the two players about the post-merger value of the combined company, a Nash-Kalai bargaining model incorporating this uncertainty is developed. This model is an improvement over those with complete certainty in that it offers improved model fit in terms of predicting the total amount paid by an acquirer, and is able to dichotomise this payment into a cash amount and a share transfer amount. The theoretical model produced some results of practical value. Firstly, a cash-only offer is never optimal. Conditions under which shares only should be tendered are identified. Secondly, the optimal offer amount depends on the form of payment and the level of perceived risk. In a share-only offer the amount is constant regardless of risk, whilst if cash is included an increase in risk will imply a decrease in the optimal amount of cash offered. The Nash-Kalai model incorporating shared uncertainty is empirically tested on the same data set used previously. This allows a comparison with earlier results and estimation of the extent of the uncertainty. An extension of this model is proposed, incorporating an alternative form of the utility functions. The second part of the thesis makes use of ideas from negotiation analysis to construct a dynamic model of the complex processes involved in negotiation. It offers prescriptive advice to one of the players on likely Pareto-optimal bargaining strategies, given a description of the strategy the other party is likely to employ. The model describes the negotiating environment and each player's negotiating strategy in terms of a few simple parameters. The model is implemented via a Monte Carlo simulation procedure, which produces expected gains to each player and average transaction values for a wide range of each of the players' strategies. The resulting two-person game bimatrix is analysed to offer general insights into negotiated outcomes, and using conventional game-theoretic and Bayesian approaches to identify "optimal" strategies for each of the players. It is shown that for the purposes of identifying optimal negotiating strategies, the players strategies (described by parameters which are continuous in nature) can be adequately approximated by a sparse grid of discrete strategies, providing that these discrete strategies are chosen so as to achieve an even spread across the set of continuous strategies. A sensitivity analysis on the contextual parameters shows that the optimal strategy pair is very robust to changes to the negotiating environment, and any such changes that have the players start negotiating from positions more removed from one another is more detrimental to the target. A conceptual decision support system which uses the model and simulated results as key components is proposed and outlined

Development of a risk-oriented strategic sourcing (ROSS) framework for the construction and electronics manufacturing industries

Strategic sourcing has increased in importance in recent years, and now plays an important role in companies’ planning. The current volatility in supply markets means companies face multiple challenges involving lock-in situations, supplier bankruptcies or supply security issues. In addition, their exposure can increase due to natural disasters, as witnessed recently in the form of bird flu, volcanic ash and tsunamis. Therefore, the primary focus of this study is risk management in the context of strategic sourcing. The study presents a literature review on sourcing based on the 15 years from 1998–2012, and considers 131 academic articles. The literature describes strategic sourcing as a strategic, holistic process in managing supplier relationships, with a long-term focus on adding value to the company and realising competitive advantage. Few studies discovered the real risk impact and status of risk management in strategic sourcing, and evaluation across countries and industries was limited, with the construction sector particularly under-researched. This methodology is founded on a qualitative study of twenty cases across Ger-many and the United Kingdom from the construction sector and electronics manufacturing industries. While considering risk management in the context of strategic sourcing, the thesis takes into account six dimensions that cover trends in strategic sourcing, theoretical and practical sourcing models, risk management, supply and demand management, critical success factors and the strategic supplier evaluation. The study contributes in several ways. First, recent trends are traced and future needs identified across the research dimensions of countries, industries and companies. Second, it evaluates critical success factors in contemporary strategic sourcing. Third, it explores the application of theoretical and practical sourcing models in terms of effectiveness and sustainability. Fourth, based on the case study findings, a risk-oriented strategic sourcing framework and a model for strategic sourcing are developed. These are based on the validation of contemporary requirements and a critical evaluation of the existing situation. It contemplates the empirical findings and leads to a structured process to manage risk in strategic sourcing. The risk-oriented framework considers areas such as trends, corporate and sourcing strategy, critical success factors, strategic supplier selection criteria, risk assessment, reporting, strategy alignment and reporting. The proposed model highlights the essential dimensions in strategic sourcing and guides us to a new definition of strategic sourcing supported by this empirical study

Resilience-Building Technologies: State of Knowledge -- ReSIST NoE Deliverable D12

This document is the first product of work package WP2, "Resilience-building and -scaling technologies", in the programme of jointly executed research (JER) of the ReSIST Network of Excellenc

Technology-assisted healthcare: exploring the use of mobile 3D visualisation technology to augment home-based fall prevention assessments

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonFalls often cause devastating injuries which precipitate hospital and long-term care admission and result in an increased burden on health care services. Fall prevention interventions are used to overcome fall risk factors in an ageing population. There is an increasing need for technology-assisted interventions to reduce health care costs, whilst also lessening the burden that an ageing population increasingly has on health care services. Research efforts have been spent on reducing intrinsic fall risk factors (i.e. functional ability deficits and balance impairments) in the older adult population through the use of technology-assisted interventions, but relatively little effort has been expended on extrinsic risk factors (i.e. unsuitable environmental conditions and lack of assistive equipment use), considering the drive for healthcare outside of the clinical setting into the patients’ home. In the field of occupational therapy, the extrinsic fall-risk assessment process (EFAP) is a prominent preventive intervention used to promote independent living and alleviate fall risk factors via the provision of assistive equipment prescribed for use by patients in their home environment. Currently, paper-based forms with measurement guidance presented in the form of 2D diagrams are used in the EFAP. These indicate the precise points and dimensions on a furniture item that must be measured as part of an assessment for equipment. However, this process involves challenges, such as inappropriate equipment prescribed due to inaccurate measurements being taken and recorded from the misinterpretation of the measurement guidance. This is largely due to the poor visual representation of guidance that is provided by existing paper-based forms, resulting in high levels of equipment abandonment by patients. Consequently, there is a need to overcome the challenges mentioned above by augmenting the limitations of the paper-based approach to visualise measurement guidance for equipment. To this end, this thesis proposes the use of 3D visualisation technology in the form of a novel mobile 3D application (Guidetomeasure) to visualise guidance in a well-perceived manner and support stakeholders with equipment prescriptions. To ensure that the artefact is a viable improvement over its 2D predecessor, it was designed, developed and empirically evaluated with patients and clinicians alike through conducting five user-centred design and experimental studies. A mixed-method analysis was undertaken to establish the design, effectiveness, efficiency and usability of the proposed artefact, compared with conventional approaches used for data collection and equipment prescription. The research findings show that both patients and clinicians suggest that 3D visualisation is a promising development of an alternative tool that contains functionality to overcome existing issues faced in the EFAP. Overall, this research makes a conceptual contribution (secondary) to the research domain and a software artefact (primary) that significantly improves practice, resulting in implications and recommendations for the wider healthcare provision (primary).The Engineering and Physical Sciences Research Council (EPSRC)