QoC Elastic Scheduling for Real-Time Control Systems

The elastic task model, a significant development in scheduling of real-time control tasks, provides a mechanism for flexible workload management in uncertain environments. It tells how to adjust the control periods to fulfill the workload constraints. However, it is not directly linked to the quality-of-control (QoC) management, the ultimate goal of a control system. As a result, it does not tell how to make the best use of the system resources to maximize the QoC improvement. To fill in this gap, a new feedback scheduling framework, which we refer to as QoC elastic scheduling, is developed in this paper for real-time process control systems. It addresses the QoC directly through embedding both the QoC management and workload adaptation into a constrained optimization problem. The resulting solution for period adjustment is in a closed-form expressed in QoC measurements, enabling closed-loop feedback of the QoC to the task scheduler. Whenever the QoC elastic scheduler is activated, it improves the QoC the most while still meeting the system constraints. Examples are given to demonstrate the effectiveness of the QoC elastic scheduling.

An entrepreneurial model of economic and environmental co-evolution

A basic tenet of ecological economics is that economic growth and development are ultimately constrained by environmental carrying capacities. It is from this basis that notions of a sustainable economy and of sustainable economic development emerge to undergird the “standard model” of ecological economics. However, the belief in “hard” environmental constraints may be obscuring the important role of the entrepreneur in the co-evolution of economic and environmental relations, and hence limiting or distorting the analytic focus of ecological economics and the range of policy options that are considered for sustainable economic development. This paper outlines a co-evolutionary model of the dynamics of economic and ecological systems as connected by entrepreneurial behaviour. We then discuss some of the key analytic and policy implications.

Adding a receding horizon to Locally Weighted Regression for learning robot control

There have been notable advances in learning to control complex robotic systems using methods such as Locally Weighted Regression (LWR). In this paper we explore some potential limits of LWR for robotic applications, particularly investigating its application to systems with a long horizon of temporal dependence. We define the horizon of temporal dependence as the delay from a control input to a desired change in output. LWR alone cannot be used in a temporally dependent system to find meaningful control values from only the current state variables and output, as the relationship between the input and the current state is under-constrained. By introducing a receding horizon of the future output states of the system, we show that sufficient constraint is applied to learn good solutions through LWR. The new method, Receding Horizon Locally Weighted Regression (RH-LWR), is demonstrated through one-shot learning on a real Series Elastic Actuator controlling a pendulum.

Manipulating task constraints to improve tactical knowledge and collective decision-making in rugby union

In team sports such as rugby union, a myriad of decisions and actions occur within the boundaries that compose the performance perceptual- motor workspace. The way that these performance boundaries constrain decision making and action has recently interested researchers and has involved developing an understanding of the concept of constraints. Considering team sports as complex dynamical systems, signifies that they are composed of multiple, independent agents (i.e. individual players) whose interactions are highly integrated. This level of complexity is characterized by the multiple ways that players in a rugby field can interact. It affords the emergence of rich patterns of behaviour, such as rucks, mauls, and collective tactical actions that emerge due to players’ adjustments to dynamically varying competition environments. During performance, the decisions and actions of each player are constrained by multiple causes (e.g. technical and tactical skills, emotional states, plans, thoughts, etc.) that generate multiple effects (e.g. to run or pass, to move forward to tackle or maintain position and drive the opponent to the line), a prime feature in a complex systems approach to team games performance (Bar- Yam, 2004). To establish a bridge between the complexity sciences and learning design in team sports like rugby union, the aim of practice sessions is to prepare players to pick up and explore the information available in the multiple constraints (i.e. the causes) that influence performance. Therefore, learning design in training sessions should be soundly based on the interactions amongst players (i.e.teammates and opponents) that will occur in rugby matches. To improve individual and collective decision making in rugby union, Passos and colleagues proposed in previous work a performer- environment interaction- based approach rather than a traditional performer- based approach (Passos, Araújo, Davids & Shuttleworth, 2008).

The ecological dynamics of decision-making in sailing

Competitive sailing is characterised by continuous interdependencies of decisions and actions. All actions imply a permanent monitoring of the environmental conditions, such as intensity and direction of the wind, sea characteristics, and the behaviour of the opponent sailors. These constraints on sailors’ behavior are in constant change implying continuous adjustments in sailors’ actions and decisions. Among the different parts of a regatta, tactics and strategy at the start are particularly relevant. Among coaches there is an adage that says that “the start is 50% of a regatta” (Houghton, 1984; Saltonstall, 1983/1986). Olympic sailing regattas are performed with boats of the same class, by one, two or three sailors, depending on the boat class. Normally before the start, sailors visit the racing venue and analyse wind and sea characteristics, in order to fine- tune their boats accordingly. Then, five minutes before the start, sailors initiate starting procedures in order to be in a favourable position at the starting line (at the “second zero”). This position is selected during the start period according to wind shifts tendencies and the actions of other boats (Figure 11.1). Only after the start signal can the boats cross the imaginary starting line between the race committee signal boat “A” and the pin end boat. The start takes place against the wind (upwind), and the boats start racing in the direction of mark 1. Based on the evaluation of the sea and wind characteristics (e.g. if the wind is stronger at a particular place on the course), sailors re- adjust their strategy for the regatta. This strategy may change during the regatta, according to wind changes and adversary actions. More to the point, strategic decisions constrain and are constrained by on- line decisions during the regatta.

Investigating child participation in the everyday talk of teacher and children in a preparatory year

In early years research, policy and education, a democratic perspective that positions children as participants and citizens is increasingly emphasized. These ideas take seriously listening to children’s opinions and respecting children’s influence over their everyday affairs. While much political and social investment has been paid to the inclusion of participatory approaches little has been reported on the practical achievement of such an approach in the day to day of early childhood education within school settings. This paper investigates talk and interaction in the everyday activities of a teacher and children in an Australian preparatory class (for children age 4-6 years) to see how ideas of child participation are experienced. We use an interactional analytic approach to demonstrate how participatory methods are employed in practical ways to manage routine interactions. Analysis shows that whilst the teacher seeks the children’s opinion and involves them in decision-making, child participation is at times constrained by the context and institutional categories of “teacher” and “student” that are jointly produced in their talk. The paper highlights tensions that arise for teachers as they balance a pedagogical intent of “teaching” and the associated institutional expectations, with efforts to engage children in decision-making. Recommendations include adopting a variety of conversational styles when engaging with children; consideration of temporal concerns and the need to acknowledge the culture of the school.

Directing Democracy : The Case of the John Lewis Partnership

The John Lewis Partnership was founded in 1929 as an “experiment in industrial democracy” (Lewis, 1948). This thesis explores the meaning of democracy in the Partnership and examines the wider implications of the case. It argues that democracy in work should be viewed as something which is intrinsically valuable because of its connection to furthering justice, equality, freedom and the rights and interests of all workers. The thesis makes three main contributions. Firstly, the production of a historically situated exploration of democratic participation in the John Lewis Partnership – the largest co-owned business in the UK. Secondly, an analysis of power relations in the organisation and an examination of the ways in which disciplinary power and regimes of truth both constrain democratic practice and offer the potential for resistance and challenge. Thirdly, the thesis challenges critics of the Partnership who have dismissed it as a form of “pseudo democracy” (Pateman, 1970: 73) and “suffocatingly paternalistic” (Ramsay, 1980: 52). Despite the constant threat of degeneration and dilution of the value framework laid down by the founder, the Partnership’s continued commitment to democratic participation provides an important contribution to our understanding of co-ownership and democratically organised forms of work. The analysis shows that management have attempted to direct and define democracy in a highly constrained way, assigning it an instrumental purpose, and privileging the ‘business case’ for democratic engagement. However, the study emphasises that the meaning of democracy is heavily contested and fraught with contradictions and paradoxes. This creates a space in which understandings of equality, solidarity and democracy are debated by the 69,000 employees who are co-owners of the business.

Stochastic simulation of chemical reactions in spatially complex media

Discrete stochastic simulations, via techniques such as the Stochastic Simulation Algorithm (SSA) are a powerful tool for understanding the dynamics of chemical kinetics when there are low numbers of certain molecular species. However, an important constraint is the assumption of well-mixedness and homogeneity. In this paper, we show how to use Monte Carlo simulations to estimate an anomalous diffusion parameter that encapsulates the crowdedness of the spatial environment. We then use this parameter to replace the rate constants of bimolecular reactions by a time-dependent power law to produce an SSA valid in cases where anomalous diffusion occurs or the system is not well-mixed (ASSA). Simulations then show that ASSA can successfully predict the temporal dynamics of chemical kinetics in a spatially constrained environment.

Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

What Could Socially-just Literacy Instruction Look Like?

Schools in Australia today are expected to improve student outcomes in an increasingly constrained context focused on accountability. At the same time as teachers work within these constraints, they are also working to ensure that all students are able to achieve quality outcomes from schooling while dealing with increasing diversity of the student population. So what is a teacher’s role in providing equitable possibilities for all of the students in their care? Teachers are left with the difficult task of balancing the many mandatory requirements placed on them, and on their students, such as gaining improvements on high stakes test scores, with the important work of dealing with individual students and student cohorts in equitable and socially just ways. This impacts on the work of all teachers, however for those teachers working in schools in contexts of complexity and duress these pressures are never greater.

An assessment of development funding for new housing post GFC in Queensland, Australia

Purpose: The purpose of this paper is to identify changes in bank lending criteria due to the GFC and to explore the associated impacts on new housing supply in Queensland, Australia. Design/methodology/approach: This research involves a survey of each of Australia’s big four banks, as well as two prominent arrangers of development finance. Data on key lending criteria was collected: Pre GFC, during the GFC, and GFC recovery stage. Findings: The GFC has resulted in a retraction of funds available for residential development. The few institutions lending are filtering out only the best credit risks by way of constrictive loan covenants including: low loan to value ratios, high cash equity requirements, regional “no go” zones, and demonstrated borrower track record. The ability of developers to proceed with new housing developments is being constrained by their inability to obtain sufficient finance. Research limitations/implications: This research uses survey data, together with an understanding of the project finance process to extrapolate impacts on the residential development industry across Queensland. No regional or sub-market analysis is included. Future research will include subsequent surveys to track any loosening of credit policies over time and sub-market sector analysis. Practical implications: The inability to obtain project finance is identified as a key constraint to new housing supply. This research will inform policy makers and provide important quantitative evidence of the importance of availability of development finance in the housing supply chain. Social implications: Queensland is facing a supply shortfall, which if not corrected, may lead to upward pressure on house prices and falling housing affordability. Originality/value: There is very little academic research on development funding. This research is unique in linking bank lending criteria to new housing supply and demonstrating the impact on the development industry.

An infinite-horizon robust filter for uncertain hidden Markov Models with conditional relative entropy constraints

We consider a robust filtering problem for uncertain discrete-time, homogeneous, first-order, finite-state hidden Markov models (HMMs). The class of uncertain HMMs considered is described by a conditional relative entropy constraint on measures perturbed from a nominal regular conditional probability distribution given the previous posterior state distribution and the latest measurement. Under this class of perturbations, a robust infinite horizon filtering problem is first formulated as a constrained optimization problem before being transformed via variational results into an unconstrained optimization problem; the latter can be elegantly solved using a risk-sensitive information-state based filtering.

An integrated framework to assess financial reward systems in construction projects

Motivation is a major driver of project performance. Despite team member ability to deliver successful project outcomes if they are not positively motivated to pursue joint project goals, then performance will be constrained. One approach to improving the motivation of project organizations is by offering a financial reward for the achievement of set performance standards above a minimum required level. However, little investigation has been undertaken into the features of successful incentive systems as a part of an overall delivery strategy. With input from organizational management literature, and drawing on the literature covering psychological and economic theories of motivation, this paper presents an integrated framework that can be used by project organizations to assess the impact of financial reward systems on motivation in construction projects. The integrated framework offers four motivation indicators which reflect key theoretical concepts across both psychological and economic disciplines. The indicators are: (1) Goal Commitment, (2) Distributive Justice, (3) Procedural Justice, and (4) Reciprocity. The paper also interprets the integrated framework against the results of a successful Australian social infrastructure project case study and identifies key learning’s for project organizations to consider when designing financial reward systems. Case study results suggest that motivation directed towards the achievement of incentive goals is influenced not only by the value placed on the financial reward for commercial benefit, but also driven by the strength of the project initiatives that encourage just and fair dealings, supporting the establishment of trust and positive reciprocal behavior across a project team. The strength of the project relationships was found to be influenced by how attractive the achievement of the goal is to the incentive recipient and how likely they were to push for the achievement of the goal. Interestingly, findings also suggested that contractor motivation is also influenced by the fairness of the performance measurement process and their perception of the trustworthiness and transparency of their client. These findings provide the basis for future research on the impact of financial reward systems on motivation in construction projects. It is anticipated that such research will shed new light on this complex topic and further define how reward systems should be designed to promote project team motivation. Due to the unique nature of construction projects with high levels of task complexity and interdependence, results are expected to vary in comparison to previous studies based on individuals or single-entity organizations.

QoS-aware web service composition using genetic algorithms

Web service technology is increasingly being used to build various e-Applications, in domains such as e-Business and e-Science. Characteristic benefits of web service technology are its inter-operability, decoupling and just-in-time integration. Using web service technology, an e-Application can be implemented by web service composition — by composing existing individual web services in accordance with the business process of the application. This means the application is provided to customers in the form of a value-added composite web service. An important and challenging issue of web service composition, is how to meet Quality-of-Service (QoS) requirements. This includes customer focused elements such as response time, price, throughput and reliability as well as how to best provide QoS results for the composites. This in turn best fulfils customers’ expectations and achieves their satisfaction. Fulfilling these QoS requirements or addressing the QoS-aware web service composition problem is the focus of this project. From a computational point of view, QoS-aware web service composition can be transformed into diverse optimisation problems. These problems are characterised as complex, large-scale, highly constrained and multi-objective problems. We therefore use genetic algorithms (GAs) to address QoS-based service composition problems. More precisely, this study addresses three important subproblems of QoS-aware web service composition; QoS-based web service selection for a composite web service accommodating constraints on inter-service dependence and conflict, QoS-based resource allocation and scheduling for multiple composite services on hybrid clouds, and performance-driven composite service partitioning for decentralised execution. Based on operations research theory, we model the three problems as a constrained optimisation problem, a resource allocation and scheduling problem, and a graph partitioning problem, respectively. Then, we present novel GAs to address these problems. We also conduct experiments to evaluate the performance of the new GAs. Finally, verification experiments are performed to show the correctness of the GAs. The major outcomes from the first problem are three novel GAs: a penaltybased GA, a min-conflict hill-climbing repairing GA, and a hybrid GA. These GAs adopt different constraint handling strategies to handle constraints on interservice dependence and conflict. This is an important factor that has been largely ignored by existing algorithms that might lead to the generation of infeasible composite services. Experimental results demonstrate the effectiveness of our GAs for handling the QoS-based web service selection problem with constraints on inter-service dependence and conflict, as well as their better scalability than the existing integer programming-based method for large scale web service selection problems. The major outcomes from the second problem has resulted in two GAs; a random-key GA and a cooperative coevolutionary GA (CCGA). Experiments demonstrate the good scalability of the two algorithms. In particular, the CCGA scales well as the number of composite services involved in a problem increases, while no other algorithms demonstrate this ability. The findings from the third problem result in a novel GA for composite service partitioning for decentralised execution. Compared with existing heuristic algorithms, the new GA is more suitable for a large-scale composite web service program partitioning problems. In addition, the GA outperforms existing heuristic algorithms, generating a better deployment topology for a composite web service for decentralised execution. These effective and scalable GAs can be integrated into QoS-based management tools to facilitate the delivery of feasible, reliable and high quality composite web services.

Beyond MOF constraints : multiple constraint set metamodelling for lifecycle management

The management of models over time in many domains requires different constraints to apply to some parts of the model as it evolves. Using EMF and its meta-language Ecore, the development of model management code and tools usually relies on the meta- model having some constraints, such as attribute and reference cardinalities and changeability, set in the least constrained way that any model user will require. Stronger versions of these constraints can then be enforced in code, or by attaching additional constraint expressions, and their evaluations engines, to the generated model code. We propose a mechanism that allows for variations to the constraining meta-attributes of metamodels, to allow enforcement of different constraints at different lifecycle stages of a model. We then discuss the implementation choices within EMF to support the validation of a state-specific metamodel on model graphs when changing states, as well as the enforcement of state-specific constraints when executing model change operations.