PhD student, Hang Yu's paper on "Pulse Arrival Scheduling for Nanonetworks Under Limited IoT Access Bandwidth" has won the Best Paper Award in the 42nd IEEE Conference on Local Computer Networks (LCN) held in Singapore 9-12 Oct 2017. We have four papers, including the Best Paper, in this conference which is ranked A by CORE/ERA since 2008.
Accepted for publication in the ACM Transactions on Embedded Computing Systems
"Coverage Preservation with Rapid Forwarding in Energy Harvesting Wireless Sensor Networks for Critical Rare Events" by David Harrison, Winston Seah and Ramesh Rayudu.
International Collaboration Success in MobiQuitous 2017!!!
Paper on "Trust-based Scheme for Cheating and Collusion Detection in Wireless Multihop Networks" by Normalia Samian and Winston Seah has been accepted by 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous) 2017.
VUW PhD scholarships
Three times a year, Victoria University of Wellington accepts applications for admission into our PhD programme with Victoria Doctoral Scholarships as well as other externally funded scholarships. The application process is managed by our Faculty of Graduate Research and details are available from their website. Applicants who are interested to do research in 5G networks, wireless networks and future internet technologies, are strongly encouraged to contact Prof Winston Seah.
Master of Engineering Scholarship on "5G Internet of Things"
The School of Engineering and Computer Science is offering a full-time Master of Engineering (ME) scholarship (domestic tuition fees plus a 1-year stipend of NZ$20,000) to an excellent candidate to work on "5G Internet of Things". This scholarship is sponsored by Victoria’s Huawei NZ Research Programme and the research will study the latest 5G wireless access technologies to support massive IoT connectivity.
The successful candidate is expected to have a good fundamental knowledge of networking, especially in medium access control protocols, random access in 5G networks, and other related topics. Knowledge of theoretical performance analysis techniques, namely, queuing theory is highly desired, and hands-on experience in common network simulation platforms (e.g. OmNet++, QualNet, etc) would be advantageous.
Interested applicants, please contact Prof Winston Seah via email attaching your transcripts, publications list, and CV. If you are suitable, you will then be provided with the information on how to apply for admission into our ME degree programme.
WiNe Research Areas
WiNe focuses on networking technology that enables the plethora of diverse devices in the Internet to communicate effectively and reliably over wireless communication, including both the wireless access as well as relevant core network technologies to achieve these goals. We study advanced networking protocols and architectures for the fast evolving Internet and 5G mobile telecommunication systems.
Wireless Networking Algorithms and Protocols: The research addresses challenging issues with environmentally friendly energy efficient algorithms and protocols for different forms of wireless networks operating in day-to-day as well as extreme conditions. Of particular interest are the MAC, RLC and random access protocols for 5G networks to support the massive number of Internet of Things (IoT) devices, and the use of network function virtualization (NFV) for resource management and optimization.
End-to-end Wired/Wireless Network Inter-connectivity: The focus of our research is on algorithms/protocols/techniques for interconnecting wireless access networks to and across the wired backbone. This research will consider the relevant core network technologies needed to provide end-to-end connectivity, focusing on latest technology trends, like Software Defined Networking (SDN), NFV, Distributed Mobility Management, as well as the core network aspect of 5G networks which has evolved towards an IP-centric network.
Wireless Network Anomaly Detection: The focus of our current research is on novel ways of detecting anomalous behaviour in wireless networks, that goes beyond security. We explore new ways of identifying and detecting anomalous network traffic that may be the precursors to attacks and other malicious activities, utilizing machine learning and deep learning.
Find out more about our Research Team and how to work with them: