Research Higher Degrees at CS3
The Centre for Complex Software Systems and Services (CS3) at Swinburne University of Technology, Melbourne, Australia, provides an exciting, high calibre, and well resourced research environment for research activities across the following research programs: Software Engineering, Intelligent Agent Technology, Web and Data Technology, Workflow Technology. Our research targets a number of application areas including service oriented systems, enterprise software systems, social software systems, and cloud computing systems. Interdisciplinary research is especially encouraged.
Applications are invited for full-time scholarships to support PhD studies. We seek highly motivated and enthusiastic candidates from the disciplines above, who wish to undertake PhD research in the area of Complex Software Systems and Services.
Scholarship Application Closing Dates are 31 May and 31 October |
Information for Applicants:
- Why you need to consider a PhD with CS3
- Scholarships Application Process
- Research Scholarship Guidelines and Applications
- Application Form
Research Topics for Potential Research Higher Degree Students at CS3:
Intelligent Agent Technology:
Project title: Resource planning for agent teams
Supervisor: Dr. Bao Vo (bvo@swin.edu.au) and Prof. Ryszard Kowalczyk (rkowalczyk@swin.edu.au)
Description: Given a team of N agents with varying capabilities and a set of tasks with different deadlines and task decomposition structures, this project investigates the mechanisms to enable a team of agents to coordinate their activities (and resources) to optimally accomplish such tasks. This problem involves both planning and scheduling for multi-agent systems.
Project title: Key Performance Indicators (KPIs) for coordinated agents' performance
Supervisor: Dr. Bao Vo (bvo@swin.edu.au) and Prof. Ryszard Kowalczyk (rkowalczyk@swin.edu.au)
Description: The success of a group of coordinated agents depends critically on each team member successfully delivering their jobs. Thus, measurement of and monitoring agents' performance will be critical for a coordinated group of agents to successfully achieve its goals. This project investigates the agents’ performance metrics to enable monitoring and assessment of agents’ performance. The project also considers other related issues include exception handling and replanning.
Project title: Multiagent planning with uncertainty
Supervisor: Dr. Bao Vo (bvo@swin.edu.au) and Prof. Ryszard Kowalczyk (rkowalczyk@swin.edu.au)
Description: Autonomous agents have been modeled by the BDI model of agency. CAN and CANPLAN are formal languages for BDI planning. But they don't deal with non-deterministic actions and uncertainty. In a multi-agent environment, agents tend to interact with one another, and an action perform by one agent might have either positive or negative effects on the actions performed by others. Thus, agents have to be able to deal with non-deterministic actions and uncertainty about the world. This project investigates this problem and introduces a framework for BDI planning with uncertainty.
Project title: Strategic Learning Agents in Equilibrium-based Markets
Supervisor: Prof. Ryszard Kowalczyk (rkowalczyk@swin.edu.au) and Dr. Bao Vo (bvo@swin.edu.au)
Description: Equilibrium-based market mechanisms in multi-agent systems offer efficient solutions for distributed coordination and resource allocation required in a range of application domains including computer networks, transportation and energy management. The objective of this research is to devise strategic learning agents and investigate their impact on the individual and social outcomes of market mechanisms based on general equilibrium theory. It involves the application of AI techniques, such as machine learning, to develop the agents’ strategic behaviour, and the theoretical and empirical evaluation of the outcomes of such strategic participants in the market-based systems.
Project title: Collective Multi-Agent Optimisation of Distributed Dynamical Systems
Supervisor: Prof. Ryszard Kowalczyk (rkowalczyk@swin.edu.au) and Dr. Bao Vo (bvo@swin.edu.au)
Description: Distributed dynamical systems are formed by a number of autonomous entities (agents) that control their own decisions and behaviour, often with little direct communication and interactions. The overall behaviour and performance of the system depends on the individual agents' behaviours and interactions with the environment that often results in an emergent behaviour of the system. The objective of this research is to devise efficient mechanisms for the collective optimisation of the performance of the system resulting from the optimisation of the individual objectives of the agents in distributed dynamical systems, such as smart energy grids. The mechanisms would be applied in smart energy management to optimise the energy usage at individual households so the individual needs and preferences are satisfied, while the goal of the system are met (e.g. constant overall demand, optimised energy generation, minimised greenhouse gas emission).
Project title: Agent-based Constrained Optimisation/Negotiation for Decentralised QoS Management of Multiple Service Compositions
Supervisor: Prof. Ryszard Kowalczyk (rkowalczyk@swin.edu.au) and Dr. Bao Vo (bvo@swin.edu.au)
Description: Services are self-contained and platform-independent software components that can be composed into new value-added services across large heterogeneous networks such as the Internet. This research focuses on adaptive management of quality-of-service (QoS) within and across multiple inter-related composite services. In particular the objective is to develop agent-based constrained optimisation and/or negotiation algorithms for decentralised QoS management between service provider agents participating in multiple service compositions at the same time, as well as to resolve conflicts in exception handling, and to self-adapt to QoS requirements within and across organisational boundaries. This research will contribute to the Service Aggregation project funded by the Smart Services CRC.
Software Engineering:
Project title: Knowledge visualisation and authoring platform
Supervisor: Prof. John Grundy (j.grundy@auckland.ac.nz)
Description: We are developing a new platform to support knowledge management in a wide variety of domains. Opportunities exist to contribute to its architecture, meta-tool components, web and mobile visualisation and authoring, data and tool integration, and to apply it to domains ranging from software engineering, health and business analytics to personal information portals. This work is a collaboration with the University of Auckland, New Zealand and several companies.
Project title: Domain-specific visual languages for cloud computing applications
Supervisor: Prof. John Grundy (j.grundy@auckland.ac.nz)
Description: We are interested in extending our Model-driven engineering and/or 3D software visualisation work to leverage emerging “cloud computing” platforms ranging from multi-core desktop PCs to highly distributed and heterogenous clouds. Research will focus on techniques to model and generate cloud-hostable services to 3D visualisation support for complex, distributed cloud applications. Tool support we aim for include performance engineering for cloud services, modelling and code generation, runt-time autonomic, reactive and adaptive support, and configuration support for end users.
Project title: Programming by example for design tool critic authoring
Supervisor: Prof. John Grundy (j.grundy@auckland.ac.nz)
Description: We have developed a novel critic authoring framework for domain-specific visual language tools. This research will extend that to enable programming-by-example techniques to specify and reuse complex design critics, using domain-specific visual languages themselves to represent critic specifications. We would like to apply the work to a wider range of DSVL design tools including spreadsheets, business process tools and web authoring tools.
Project title: Model-driven engineering for adaptive user interfaces and services
Supervisor: Prof. John Grundy (j.grundy@auckland.ac.nz)
Description: We have developed a number of techniques for modelling and generating complex user interfaces that can be run on a variety of devices including conventional web browsers to mobile applications. This research will extend this earlier work to improve modelling capabilities using domain-specific visual languages, investigate new ways to generate, test and evolve interfaces and back-end services including end user computing support, and apply to different domains e.g. health, business processes, manufacturing and diverse mass-market end user applications.
Project title: Probabilistic Verification and Model-Based Quality Evaluation
Supervisor: Dr. Lars Gunske (lgrunske@swin.edu.au)
Description: Model Based Development (MBD) has established itself as the key approach to software engineering of increasingly complex systems in the automotive and aerospace domain. It has proved successful at managing complexity associated with functionality. A new approach is to use model-based techniques also for quality evaluation and predictions. Since most of quality attributes such as performance, reliability, availability, safety, and security have a probabilistic nature, probabilistic verification techniques are the best solution to perform model-based quality evaluation. The research project shall explore the possibilities of probabilistic modelling and verification techniques to reason about quality attributes early in the software development lifecycle.
Project title: Empirical Evaluation of Property Specification Patterns
Supervisor: Dr. Lars Gunske (lgrunske@swin.edu.au)
Description: Formal verification is essential for many systems (e.g. automotive, avionic, and medical system) and a formal specification of the required properties is needed. This research project aims to investigate with empirical experiments if using specification patterns (specifically the specification patterns of Dwyer et al. 99) has a positive impact on the ability of software engineers to formalize requirements and properties. The used specification formalisms are temporal logics.
Project title: Probabilistic Failure Mode and Effect Analysis for Medical Processes
Supervisor: Dr. Lars Gunske (lgrunske@swin.edu.au)
Description: Failure mode and effects analysis (FMEA) is a technique to reason about possible system hazards that result from system or system component failures. Probabilistic FMEA (pFMEA) automates FMEA with fault injection experiments and probabilistic model checking. However, it is currently only applied to systems and not to processes. The proposed project shall investigate the applicability of pFMEA to processes with formal process descriptions. The aim of this research project is to create a theoretical basis process-based pFMEA and validate the theory with real world medical processes (e.g. blood transfusion processes, patient registration).
Project title: Adaptive Service Delivery
Supervisor: Prof. Jun Han (jhan@swin.edu.au) and Dr. Alan Colman (acolman@swin.edu.au)
Description: In another research project funded by the Smart Services CRC, CS3 researchers are investigating new ways of service delivery in the service marketplace (or ecosystem), connecting service providers and service consumers. In particular, it considers how to re-purpose and reconfigure services and service assemblies for different business application contexts and manage their variation during operation. This will result in methods and tools enabling service delivery in a flexible and adaptive manner, creating increased business value for service providers, consumers and distributors.
Project title: Context-aware Vehicle Software Systems
Supervisor: Prof. Jun Han (jhan@swin.edu.au) and Dr. Alan Colman (acolman@swin.edu.au)
Description: With support from the AutoCRC, a CS3 research team is investigating a new context-aware pervasive computing platform for seamlessly managing and integrating in-vehicle functions and external services. The research adopts a service-oriented approach, which is particularly suited to managing such open, dynamic and adaptive systems. It will lead to enhanced driver experience and increased vehicle control and safety through distraction-free vehicle-environment interaction.
Project title: Service Oriented Architecture for IT Infrastructure Management
Supervisor: Prof. Jun Han (jhan@swin.edu.au)
Description: Funded by the ARC with support and collaboration from CA, a research team from the Centre is engaged in research into the next generation Service Registries, which will be the centre piece of any future enterprise information systems deploying the service-oriented architecture. These registries support capability (business and application)-based service modelling, publication, discovery and composition, and facilitate adaptive lifecycle management of the services and applications and their auditing and legal compliance from an enterprise perspective.
Project title: Large-Scale Enterprise Systems Emulation
Supervisor: Prof. Jun Han (jhan@swin.edu.au)
Description: With support and collaboration from CA, researchers from the Centre are investigating advanced techniques to emulate simultaneously a large number of large-scale enterprise information systems with various and varied behaviours in diverse real-world deployment environments. One particular application of this emulation platform will be the provision of a testing environment for large-scale integration of enterprise systems.
Web and Data Technology:
Project title: Keyword search over XML data
Supervisor: Prof. Chengfei Liu (cliu@swin.edu.au)
Description: Conventional keyword search techniques have been proven user-friendly and effective for searching HTML documents; however, they are far from meeting users’ requirement for querying XML data. The most challenging issue is to find meaningful and relevant entities in XML documents. This project aims to provide novel and effective solutions to the problem by developing effective methods for identifying, inferring and ranking returned entities, and efficient algorithms for finding meaningful entities and top-k results.
Project title: Processing queries in probabilistic XML or RDF databases
Supervisor: Prof. Chengfei Liu (cliu@swin.edu.au)
Description: The flexibility of XML or RDF data models allows a more natural representation of uncertain data compared with the relational model, and the matching of XML or RDF queries against probabilistic XML or RDF data is essential, with those answers of top-k probabilities especially useful to users. This project aims to find efficient algorithms for finding answers for top-k queries.
Project title: Artifact-centric approach to workflow management
Supervisor: Prof. Chengfei Liu (cliu@swin.edu.au)
Description: Traditional process-centric workflow models fall short in supporting several features in business modelling, such as flexibility and adaptability, componentization, workflow evolution. These features can be easily supported by the so-called the artefact-centric workflow models, which focus on business-relevant objects and their lifecycles. This project aims to investigate several issues in this new approach ranging from design methodology to run-time enactment support.
Workflow Technology:
Project title: Cloud computing based scientific and business workflows
Supervisor: Prof. Yun Yang (yyang@swin.edu.au) & Dr Jinjun Chen (jchen@swin.edu.au), CS3
Description: Processes are everywhere. Workflow systems are facilitated to support processes. In this broad area, several interrelated PhD topics are listed which can be conducted by individual candidates. One of the current foci is the cloud computing based scientific and business workflows, so called cloud workflows, which includes research on cloud computing systems in general and their support to workflows in particular. The innovative topics in workflows span from modelling, architecture, scheduling, data management, verification and exception handling to security and trust.
Project title: Service-oriented computing
Supervisor: Prof. Yun Yang (yyang@swin.edu.au) & Dr Jinjun Chen (jchen@swin.edu.au), CS3
Description: The full potential of service-oriented computing can be achieved only when consumers can use services that fit the context in which they are used. This motivates effective management of services with sophisticated control mechanisms to cater for differentiated quality of service offerings. This project aims to provide cutting edge IT solutions for effective management of services during their lifetime to ensure that the "right" services are used throughout the service provision.
