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.

Developing a model of embedding academic numeracy in university programs : a case study from nursing

This is a study of the academic numeracy of nursing students. This study develops a theoretical model for the design and delivery of university courses in academic numeracy. The following objectives are addressed: 1. To investigate nursing students' current knowledge of academic numeracy; 2. To investigate how nursing students’ knowledge and skills in academic numeracy can be enhanced using a developmental psychology framework; and 3. To utilise data derived from meeting objectives 1 and 2 to develop a theoretical model to embed academic numeracy in university programs. This study draws from Valsiner’s Human Development Theory (Valsiner, 1997, 2007). It is a quasi-experimental intervention case study (Faltis, 1997) and takes a multimethod approach using pre- and post-tests; observation notes; and semi-structured teaching sessions to document a series of microgenetic studies of student numeracy. Each microgenetic study is centered on the lived experience of students becoming more numerate. The method for this section is based on Vygotsky’s double stimulation (Valsiner, 2000a; 2007). Data collection includes interviews on students’ past experience with mathematics; their present feelings and experiences and how these present feelings and experiences are transformed. The findings from this study have provided evidence that the course developed for nursing students, underpinned by an appropriate framework, does improve academic numeracy. More specifically, students improved their content knowledge of and confidence in mathematics in areas that were directly related to their degree. The study used Valsiner’s microgenetic approach to development to trace the course as it was being taught and two students’ personal academic numeracy journeys. It highlighted particularly troublesome concepts, then outlined scaffolding and pathways used to develop understanding. This approach to academic numeracy development was summarised into a four-faceted model at the university, program, course and individual level. This model can be applied successfully to similar contexts. Thus the thesis advances both theory and practice in this under-researched and under-theorised area.

Actioning university-community engagement : leadership, mentoring and professional communities

This presentation focuses on actioning university-community engagement through a Department of Employment, Education and Work Relations (DEEWR) grant. The project associated with this grant is titled Teacher Education Done Differently (TEDD) and it is currently in its third and final year of operation. TEDD aims to facilitate benefits for all partners (i.e., teachers, school executives, students, preservice teachers, university staff, and education departments). This project aims to facilitate understandings and skills on advancing mentoring and teaching practices for preservice teachers.

Orientation passport : using gamification to engage university students

Adding game elements to an application to motivate use and enhance the user experience is a growing trend known as gamification. This study explores the use of game achievements when applied to a mobile application designed to help new students at university. This paper describes the foundations of a design framework used to integrate game elements to Orientation Passport, a personalised orientation event application for smart phones. Orientation Passport utilises game achievements to present orientation information in an engaging way and to encourage use of the application. The system is explained in terms of the design framework, and the findings of a pilot study involving 26 new students are presented. This study contributes the foundations of a design framework for general gamified achievement design. It also suggests that added game elements can be enjoyable but can potentially encourage undesirable use by some, and aren't as enjoyable if not enforced properly by the technology. Consideration is also needed when enforcing stricter game rules as usability can be affected.

University students’ depression : a cross-cultural investigation

Australian, Iranian and Portuguese university students (N = 967) completed University Students Depression Inventory (USDI; Khawaja & Bryden, 2006) in English, Persian, and Portuguese languages respectively. A series of MANOVA were used to examine differences in depression symptoms as an effect of the country and demographic variables. Interactions were also examined. The results indicated that country, gender, and year level had some impact on the depressive symptoms of the university students. Australian students were more depressed than the Iranian and Portuguese students, while Iranian students were more depressed than the Portuguese students. Subscales of USDI: Lethargy, Motivation, and Cognitive/Emotional were also used to compare the depressive symptoms of students. The Australian female students reported a significantly higher level of lethargy than their male counterparts. Similarly, the first year male students from Iran were significantly more lethargic than the first year Iranian female students. Iranian and Portuguese male students, compared to the female students of these countries, experienced a lower level of motivation. The Australian and Iranian students, compared to the Portuguese students, reported a significantly higher level of cognitive and affective symptoms. The scores on the Cognitive/Emotional subscale increased with the year level. Differences among students’ depression are described and implications discussed.

Converting theory to practice : university-school collaboration on devising strategies for mentoring pedagogical knowledge

There appears no shortage of theorists for preservice teacher education; however many ideas are abandoned without practical applications. Indeed, it can take years for theories to materialise into practice, if they materialise at all. The quality of preservice teacher education is central for enhancing an education system, and mentors’ roles can assist to shape preservice teachers’ development within the school context. Yet mentoring can be haphazard without being underpinned by a theoretical framework. A mentoring model (personal attributes, system requirements, pedagogical knowledge, modelling, and feedback) has emerged from research and the literature to guide mentors’ practices. This qualitative study investigates mentors’ pedagogical knowledge as one factor crucial to the mentoring process. More specifically, this study involves a questionnaire and audio-recorded focus group meetings with experienced mentors (n=14) who deliberated on devising practical applications for mentoring pedagogical knowledge. Findings revealed that these experienced mentors pinpointed practical applications around a mentor’s role for providing pedagogical knowledge to the mentee. These strategies were varied and demonstrated that any one mentoring practice may be approached from a number of different angles. Nevertheless, there were core mentoring practices in pedagogical knowledge such as showing the mentee how to plan for teaching, articulating classroom management approaches, and talking about how to connect learning to assessment. Mentors may require education on current mentoring practices with practical strategies that are linked to theoretical underpinnings.

Application of operations research techniques to improve efficiency in the emergency department

The main aim of this thesis is to analyse and optimise a public hospital Emergency Department. The Emergency Department (ED) is a complex system with limited resources and a high demand for these resources. Adding to the complexity is the stochastic nature of almost every element and characteristic in the ED. The interaction with other functional areas also complicates the system as these areas have a huge impact on the ED and the ED is powerless to change them. Therefore it is imperative that OR be applied to the ED to improve the performance within the constraints of the system. The main characteristics of the system to optimise included tardiness, adherence to waiting time targets, access block and length of stay. A validated and verified simulation model was built to model the real life system. This enabled detailed analysis of resources and flow without disruption to the actual ED. A wide range of different policies for the ED and a variety of resources were able to be investigated. Of particular interest was the number and type of beds in the ED and also the shift times of physicians. One point worth noting was that neither of these resources work in isolation and for optimisation of the system both resources need to be investigated in tandem. The ED was likened to a flow shop scheduling problem with the patients and beds being synonymous with the jobs and machines typically found in manufacturing problems. This enabled an analytic scheduling approach. Constructive heuristics were developed to reactively schedule the system in real time and these were able to improve the performance of the system. Metaheuristics that optimised the system were also developed and analysed. An innovative hybrid Simulated Annealing and Tabu Search algorithm was developed that out-performed both simulated annealing and tabu search algorithms by combining some of their features. The new algorithm achieves a more optimal solution and does so in a shorter time.

‘It's the end of the university as we know it (and I feel fine)’: the Generation Y student in higher education discourse

This paper examines discussions of Generation Y within higher education discourse, arguing the sector’s use of the term to describe students is misguided for three reasons. First, portraying students as belonging to Generation Y homogenises people undertaking higher education as young, middle-class and technologically literate. Second, speaking of Generation Y students allows constructivism to be reinvented as a ‘new’ learning and teaching philosophy. Third, the Generation Y university student has become a central figure in concerns about technology’s role in learning and teaching. While the notion of the ‘Generation Y student’ creates the illusion that higher education institutions understand their constituents, ultimately, it is of little value in explaining young adults’ educational experiences.

ICT for blended learning Queensland University of Technology, Australia

This report focuses on blended learning within the Queensland University of Technology (QUT) which is one of Australia’s largest public universities. Although the university in its current format was established in 1989, it contains several previous institutions that can be traced to the earliest forms of technical and teacher education in Queensland in the 19th century (Kyle et al., 1999). The focal point of the report is the experience of QUT’s Faculty of Education which was formed from the amalgamation of several teacher training colleges servicing pre-school and kindergarten, primary and secondary teacher education. While the broader university currently employs approximately 4,000 staff and has about 40,000 students, QUT’s Faculty of Education employs around 170 staff and has approximately 5,000 enrolled students. The Faculty of Education at QUT is the largest provider of pre-service teacher education in Australia and is one of the largest producers of educational research. A major theme of the Faculty of Education is its focus on education and research that provides teachers, schools and educational authorities with practical solutions to the multifaceted issues facing contemporary education.

The ascendancy of oracy in university courses: Implications for teachers and second language users

This chapter reports on a study of oracy in a first-year university Business course, with particular interest in the oracy demands for second language-using international students. The research is relevant at a time when Higher Education is characterised by the confluence of increased international enrolments, more dialogic teaching and learning, and imperatives for teamwork and collaboration. Data sources for the study included videotaped lectures and tutorials, course documents, student surveys, and an interview with the lecturer. The findings pointed to a complex, oracy-laden environment where interactive talk fulfilled high-stakes functions related to social inclusion, the co-construction of knowledge, and the accomplishment of assessment tasks. The salience of talk posed significant challenges for students negotiating these core functions in their second language. The study highlights the oracy demands in university courses and foregrounds the need for university teachers, curriculum writers and speaking test developers to recognise these demands and explicate them for the benefit of all students.

Scheduling Trains with Priorities : a no-wait blocking parallel-machine job-shop scheduling model

The paper investigates train scheduling problems when prioritised trains and non-prioritised trains are simultaneously traversed in a single-line rail network. In this case, no-wait conditions arise because the prioritised trains such as express passenger trains should traverse continuously without any interruption. In comparison, non-prioritised trains such as freight trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available, which is thought of as a relaxation of no-wait conditions. With thorough analysis of the structural properties of the No-Wait Blocking Parallel-Machine Job-Shop-Scheduling (NWBPMJSS) problem that is originated in this research, an innovative generic constructive algorithm (called NWBPMJSS_Liu-Kozan) is proposed to construct the feasible train timetable in terms of a given order of trains. In particular, the proposed NWBPMJSS_Liu-Kozan constructive algorithm comprises several recursively-used sub-algorithms (i.e. Best-Starting-Time-Determination Procedure, Blocking-Time-Determination Procedure, Conflict-Checking Procedure, Conflict-Eliminating Procedure, Tune-up Procedure and Fine-tune Procedure) to guarantee feasibility by satisfying the blocking, no-wait, deadlock-free and conflict-free constraints. A two-stage hybrid heuristic algorithm (NWBPMJSS_Liu-Kozan-BIH) is developed by combining the NWBPMJSS_Liu-Kozan constructive algorithm and the Best-Insertion-Heuristic (BIH) algorithm to find the preferable train schedule in an efficient and economical way. Extensive computational experiments show that the proposed methodology is promising because it can be applied as a standard and fundamental toolbox for identifying, analysing, modelling and solving real-world scheduling problems.

A hybrid shifting bottleneck procedure algorithm for the parallel-machine job-shop scheduling problem

In practice, parallel-machine job-shop scheduling (PMJSS) is very useful in the development of standard modelling approaches and generic solution techniques for many real-world scheduling problems. In this paper, based on the analysis of structural properties in an extended disjunctive graph model, a hybrid shifting bottleneck procedure (HSBP) algorithm combined with Tabu Search metaheuristic algorithm is developed to deal with the PMJSS problem. The original-version SBP algorithm for the job-shop scheduling (JSS) has been significantly improved to solve the PMJSS problem with four novelties: i) a topological-sequence algorithm is proposed to decompose the PMJSS problem into a set of single-machine scheduling (SMS) and/or parallel-machine scheduling (PMS) subproblems; ii) a modified Carlier algorithm based on the proposed lemmas and the proofs is developed to solve the SMS subproblem; iii) the Jackson rule is extended to solve the PMS subproblem; iv) a Tabu Search metaheuristic algorithm is embedded under the framework of SBP to optimise the JSS and PMJSS cases. The computational experiments show that the proposed HSBP is very efficient in solving the JSS and PMJSS problems.

Scheduling a flow-shop with combined buffer conditions

In this paper, No-Wait, No-Buffer, Limited-Buffer, and Infinite-Buffer conditions for the flow-shop problem (FSP) have been investigated. These four different buffer conditions have been combined to generate a new class of scheduling problem, which is significant for modelling many real-world scheduling problems. A new heuristic algorithm is developed to solve this strongly NP-hard problem. Detailed numerical implementations have been analysed and promising results have been achieved.