Important notice: I have moved to University of Technology Sydney effective from February 2014 and taken a position of Professor of Wireless Networking, Director of University Center for Real-time Information Networks at UTS, which is among the largest and strongest research center in Australia in the field of wireless networking. I continute to supervise research students at University of Technology Sydney. You can reach me via my webpage at UTS, my personal webpage or at firstname.lastname@example.org. This page may no longer be updated.
- Scholarship Opportunities
- Funded Research Projects
- Research Students
- Research Projects
- Applied Graph Theory and Its Applications in Wireless Networks
- Large-Scale Highly Dynamic Wireless Networks: Architecture and Communication Strategies Design
- Wireless Localization Techniques
- Spatially Distributed Complex Multiagent Systems
- Quality of Service in 4G Wireless Network
- Multiple Time Scale Traffic Engineering
I have a couple of scholarships for PhD students funded by my research projects now. If you have a strong academic record and are interested in taking the challenges in the broad area of wireless network, wireless sensor network, network traffic measurement and analysis and network performance analysis, please drop me an email.
Update February 2014: Please note that I have two full scholarships for PhD students available. For international students, in addition to living expense, the scholarship also include tuition fee waiver scholarship. You may find detailed information here or in the PDF document. Please drop me an email if you require more information.
You may also consider the following university funded and government funded scholarships.
If you are an Australian Permanent Resident or Citizen, you may consider applying for a University Postgraduate Scholarship or Australian Postgraduate Award. Further information can be found at http://www.usyd.edu.au/fstudent/scholarships.shtml .
If you are an international student with a good academic record, you may consider the International Postgraduate Student Scholarship. Further information can be found at http://www.usyd.edu.au/fstudent/scholarships.shtml .
Chinese Scholarship Council Postgraduate Scholarships Program
Applications are welcome from students funded by the Chinese Scholarship Council (CSC) scheme. CSC student may apply either as a visiting student or as an enrolled PhD student at Australian University. In the latter case, a tuition waiver will be granted on competitive basis.
-------Funded Research Projects------
Funded research projects for which I am a Chief Investigator:
- “Distributed Control and Estimation in Networked Environments”, National ICT Australia (NICTA) - Defence Science and Technology Organization (DSTO) joint project award, $346,737, (2012-2014).
- “Large-scale highly dynamic wireless networks: architecture and communication strategies design”, ARC Discovery Project, $300,000, (2012-2014).
- “Spatially distributed complex multiagent systems”, ARC Discovery Project, $600,000, (2011-2015).
- “Robust Multi-Agent Sensor Network Systems”, US Air Force, Asian Office of Research and Development, US$180,000, (2010-2011).
- “Measuring and ensuring performance and information quality in multi-agent sensor network systems”, US Air Force, Asian Office of Research and Development, $43,000, (2009).
- “Coordination, Control, Localization and Health Characterization of Autonomous Multi-Agent Swarms”, Joint National ICT Australia (NICTA) - Defence Science and Technology Office Research (DSTO) project, $1,239,000, (2008-2011).
- “A Graph Theoretical Approach to Cooperative Radio Resource Management”, The University of Sydney Bridging Support Grant, $50,000, (2008).
- “Large Scale Complex Multiagent Systems : Control Methodologies and Information Architectures”, ARC Discovery Project, $661,000, (2008-2010).
- “A unified framework for analyzing the timescale of interest for traffic measurements, modelling and performance analysis”, ARC Discovery Project, $150,000, (2005-2007).
- “A Quality of Service Monitoring System for Service Level Agreement Verification”, Optus contracted research project, $40,715, (2004-2005).
- “Characterization, Diagnosis, and Assurance of Health and Quality of Sensor Formations”, NICTA-DSTO joint research project, $866,157, (2005-2008).
- “Design of Video Transmission System Over IEEE Wireless Local Area Network", University of Sydney Research and Development Grant, $19,000, (2006).
- Two William Girling Waston traveling grant, (2004).
- “Distributed location estimation algorithms for wireless sensor networks”, University of Sydney Research and Development grant, $20,000, (2005).
- “Location Estimation in Sensor Network”, National ICT Australia Research Project Award, $25,500, (2005-2007).
- “Development of 4G wireless communication systems and wireless sensor networks”, ARC Linkage Infrastructure, Equipment and Facilities, $200,000, (2007).
-------My Research Students (as the Principal Supervisor)------
- Mr. Peng Wang, PhD candidate (funded by ARC project and NIP top-up scholarship)
- Ms. Ruixue Mao, Research Master (funded by ARC project and NIP top-op scholarship)
- Ms. Yang Tao, PhD candidate (funded by ARC project and NIP top-up scholarship)
- Mr. Seh Chun Ng, PhD candidate (thesis submitted in 2012, funded by EIPRS scholarship, NICTA top-up scholarship and NIP top-up scholarship)
- Mr. Zijie Zhang, PhD candidate (completed in 2012, funded by ARC scholarship and NIP top-up scholarship, working as a research fellow at NICTA after graduation)
- Ms. Anushiya Kannan, PhD candidate (completed PhD in 2010, working as a Research Fellow at University of New South Wales after graduation, funded by UPA scholarship, NICTA top-up scholarship and NIP top-up scholarship)
- Mr. Xiaoyuan Ta, Master and PhD candidate (completed Master in 2006 and PhD in 2009, funded by UPA scholarship, NICTA top-up scholarship, NIP top-up scholarship, My Optus project and my ARC project, now working in a financial company as a quantitative analyst in Hong Kong)
- Mr. Lixiang Xiong, PhD candidate (completed PhD in 2008, now working at Australian Communications and Media Authority (ACMA), funded by APA scholarship, NICTA top-up scholarship, NIP top-up scholarship and my ARC project)
- Mr. Yanqiang Luan, Research Master (completed in 2005, funded by my ARC project, now working in Motorola Mobility, China, as a software development team leader)
-------Visiting Students Under My Supervision-------
- Ms. Xuefei Zhang, Beijing University of Posts and Telecommunications, 2013-2014
- Ms. Jindi Li, Wuhan University of Science and Technology, 2013-2014
- Mr. Bing Yang, Huazhong University of Science and Technology, 2013-
- Mr. Kun Wei, Shanghai Research Center for Wireless Communications, Chinese Academy of Science, 2013
- Ms. Xue Han, Research Center for Wireless Communications Technology, Chinese Academy of Science, Beijing, 2012
-------Current Research Projects------
Communication Network Design for Complex Intelligent Transport Systems
The last two decades have witnessed unprecedented growth in telecommunications. This development in telecommunications opens doors to many sophisticated complex systems, e.g. intelligent transport systems (ITS), smart grids and social networks, that previously were not feasible. With the deeper penetration of telecommunications technology into these systems, people have come to realize that, instead of treating the communication network and the complex system served by the communication network as two separate entities with one demanding communication services from the other, a seamlessly integrated system can lead to an even greater benefit and in many cases is a perquisite for both systems to perform satisfactorily. With few exceptions, existing communication networks have not been designed to integrate with the complex systems and these complex systems are merely treated as consumers of communication networks posing some specific bandwidth and delay requirements.
In this research, using intelligent transport systems as a representative example of a category of dynamic and evolving complex systems, we shall develop tools for communication network design to cater for the intricate demands of these complex systems and to integrate and exploit the characteristics and dynamics of complex systems.
Applied Graph Theory and Its Applications in Wireless Networks
Wireless multi-hop networks, in various forms, e.g. wireless sensor networks, underwater sensor networks, vehicular networks, mesh networks and UAV (Unmanned Aerial Vehicle) formations, and under various names, e.g. ad-hoc networks, hybrid networks, delay tolerant networks and intermittently connected networks, are being increasingly used in military and civilian applications. Graph theory, particularly a recently developed branch of graph theory, i.e. random geometric graphs, is well suited to studying these problems. These include but not limited to: cooperative communications; opportunistic routing; geographic routing; statistical characterization (e.g. connectivity, capacity and delay) of multi-hop wireless networks; geometric constraints among connected nodes and their use in autonomous parameter estimation without manual calibration. This research will investigate the use of graph theory to solve problems in the above broad areas. Research outcomes will benefit almost all areas in wireless multi-hop networks, including routing, scheduling, mobility management, dimensioning, interference control, energy management and localization.
Large-Scale Highly Dynamic Wireless Networks: Architecture and Communication Strategies Design
We are on the brink of a new era in wireless communications, brought on by the proliferation of wireless devices and the emergence of new types of communication systems such as IEEE 802.11p based Vehicular Networks, IEEE 802.15 based Wireless Personal Area Networks, IEEE 802.11s based Mesh Networks and IETF RFC4838 based Delay Tolerant Networks. Among the most exciting, challenging and important communications problems today are those involving large-scale highly dynamic wireless networks, particularly wireless vehicular networks for autonomous vehicles (also known as driverless or self-driving cars). The social and economical benefits of autonomous vehicles are numerous: reducing traffic congestion, saving fuels and reducing greenhouse gas emission, freeing drivers and improving productivity, helping reconnect the elderly and disabled to our society, and the most compelling benefit is of course improving road safety and saving lives – in Australia alone the number of serious injury accidents every year is over 25,000 and 1507 people lost their lives in Australian roads in 2009.
This project proposes to develop scientific tools for the modelling, characterization, network architecture design and communication strategies design of highly dynamic networks, with a particular focus on highly dynamic vehicular networks for autonomous vehicles. The aim is to develop fundamental methodologies, built on a solid understanding of the characteristics of these networks, that provide design principles and management guidelines for these networks.
The following topic areas will be investigated (but not limited to):
- Characterization of dynamic networks.
- Network architecture design.
- Building local consensus.
- Statistical radio resource management.
- Cooperative communication strategy.
Wireless Localization Techniques
Wireless sensor networks are a significant technology attracting considerable research attention in recent years. It is one of the most important technologies for the 21st century. Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power and multi-functional sensor nodes that are small in size and communicate in short distances. These tiny sensor nodes, which consist of sensing, data processing, and communicating components, bring the idea of wireless sensor networks into reality. Sensor networks represent a significant improvement over traditional sensors. Cheap, smart sensors, networked through wireless links and deployed in large numbers, provide unprecedented opportunities for monitoring and controlling homes, cities, and the environment. In addition, networked sensors have a broad spectrum of applications in the defense area, generating new capabilities for reconnaissance and surveillance as well as other tactical applications.
Emerging applications for wireless sensor networks will depend on automatic and accurate location of thousands of sensors. In environmental sensing applications such as bush fire surveillance, water quality monitoring, precision agriculture, and indoor air quality monitoring, “sensing data without knowing the sensor location is meaningless”. In addition, location estimation may enable applications such as inventory management, intrusion detection, traffic monitoring, and telecare, etc. In this research we shall investigate distributed location estimation algorithms in wireless sensor networks and its applications. Particularly we will both investigate theoretical problems in the area of large-scale sensor network localization and develop various localization techniques to solve practical problems encountered by our industrial partners in various application scenarios.
Spatially Distributed Complex Multiagent Systems
Among the most exciting, challenging and important control and communications problems today are those involving large-scale, multi-agent systems, often with spatially distributed physical agents. Examples include vehicular networks, formations of unmanned airborne vehicles, sensor networks for pollution, biological or border control, etc. The ultimate technical challenge flows from the architectures, often multiple architectures, for sensing, communications and control respectively; being decentralized and distributed, they were hardly ever studied in earlier decades. This research is aimed squarely at developing design methodologies for such systems, focusing on architectural fundamentals. For the sake of concreteness, the principal problem instantiations we will consider are formation control, and wireless networks, especially sensor networks and mobile multi-hop networks. The examples are linked operationally and theoretically, e.g., agents such as unmanned airborne vehicles (UAVs) in a moving formation are commonly part of a network of sensors, and tools of graph theory will underpin the solution of many problems in the two areas.
Particularly, we shall investigate the following topic areas (but not limited to):
- Wireless Networks: three key problems
- Mobile multi-hop networks: fundamental trade-offs.
- Mobile network localization.
- ‘Local’ localization for mobile and static networks
- Formation Motion Control
- Effective shape control algorithms.
- Global behavior of control systems.
Quality of Service in 4G Wireless Network
Value-added services such as multimedia services are becoming the fastest growing revenue-generating sector in telecommunications industry. With the explosive growth of the mobile communication and the expansion of Internet services, multimedia services are expected for future mobile communication systems. As 3G is still not sufficient to support future mobile communication strategy, it is time to discuss the development of the future generation mobile communication systems.
4G wireless network is going to be a high speed, IP based network, supporting a variety of services and seamless mobility between different access technologies (e.g. wireless LAN, W-CDMA). Providing Quality of Service (QoS) demanded by the multimedia services in the 4G network is a challenging problem.
This project will investigate QoS solutions in the 4G network. The objective of this research is to provide robust and uniform QoS to multimedia services across heterogeneous networks in 4G.
Multiple Time Scale Traffic Engineering
Today's Internet service providers (ISPs) are required to provide the best network service at the minimum cost in order to attract new customers and to retain the existing ones. This means that an ISP is expected to run a highly reliable network with consistently good performance by utilising its existing network resources as efficiently as possible. For this purpose, an ISP utilises a repertoire of tools, which is collectively known as traffic engineering, to achieve this goal. Traffic engineering makes use of a number of different traffic control mechanisms. Some examples are active queue management, admission control, load balancing and routing. These different mechanisms exist, not only because they serve different purposes, but also because they only operate effectively over one particular network timescale, i.e. packet level, burst level and connection level. Moreover traffic engineering at each timescale works separately without any coordination.
A small timescale allows traffic engineering to better track traffic changes to respond to congestion in a timely manner. However, this can cause frequent route changes which can deteriorate the performance of the applications running over the network. In addition, traffic information has to be disseminated in the network frequently and this puts additional load onto the network. On the other hand, a large timescale can provide stable routing which is important in maintaining good performance of network applications and imposes less burden on the network for traffic load information dissemination. However, it cannot deal with short term traffic surge. Thus, in choosing between a small or large timescale, a tension exists between routing stability and capability to cope with short-term network congestion.
The fundamental problem of this dilemma is caused by using only one single timescale and can effectively be removed if both small timescale and large timescale traffic engineering can be unified into one framework as proposed here. This project breaks away from the traditional traffic engineering paradigm which takes only one timescale into account to a new paradigm which takes multiple timescales into consideration. In this project, we plan to investigate a new architecture where the long term traffic control decisions are made centrally while the short term ones are made distributedly. A challenging research problem is to ensure that these decisions work together to enhance the overall network problems rather than working against each other.