Chan Mun Choon
I graduated with a BS in Computer and Electrical Engineering from Purdue University and Ph.D. from Columbia University. I was a Member of Technical Staff in the Networking Research Laboratory, Bell Labs, Lucent Technologies before joining NUS. I am currently a Professor in the Department of Compuer Science, School of Computing.
- School of Computing, National University of Singapore
- Office: COM3 #02-15
- Tel: +65 6516 7372
- Email: chanmc AT comp dot nus dot edu dot sg
I am looking to offer research projects in the areas related to programming networks (DPTP
) and 5G network (FSA
Research advances in Software Defined Networking (SDN) have enabled new paradigms and architectures through providing programmable capabilities to both the control and data plane. I am particularly interested in understanding how these capabilities enable new monitoring frameworks, control paradigms, virtualization strategies and speedup of large scale distributed computations. I am also involved in the bare-metal provisioning of SDN testbed on the National Cybersecurity R&D Lab (NCL) (http://ncl.sg).
- CH Song, XZ Khooi, DM Divakaran, MC Chan, Revisiting Application Offloads on Programmable Switches, IFIP Networking, June 2022 pdf
- N Budhdev, R Joshi, PG Kannan, MC Chan, T Mitra, FSA: fronthaul slicing architecture for 5G using dataplane programmable switches, ACM MOBICOM 2021. pdf
- PG Kannan, N Budhdev, R Joshi, MC Chan, Debugging Transient Faults in Data Center Networks using Synchronized Network-wide Packet Histories, USENIX conference on Networked Systems Design and Implementation (NSDI), April 2021. pdf
- CH Song, PG Kannan, BKH Low, MC Chan, FCM-sketch: generic network measurements with data plane support, CoNEXT, Dec 2020. pdf
- T. Qu, R. Joshi, MC. Chan, B. Leong, D. Guo, Z. Liu, SQR: In-network Packet Loss Recovery from Link Failures for Highly Reliable Datacenter Networks, International Conference on Network Protocols (ICNP) Oct 2019 (Best Paper). pdf
- PG Kannan, R Joshi, MC Chan, Precise Time-synchronization in the Data-Plane using Programmable Switching ASICs, Proceedings of the 2019 ACM Symposium on SDN Research. (Best Paper), April 2019. pdf
Low Power, Energy Efficient Edge Computing
With mobile devices becoming ubiquitous, collaborative applications have become increasingly pervasive. We look into various approaches in which these devices can leverage the available sensing, computation and communication capabilities to design collaborative applications. In particular, we are looking at how high-fidelity context awareness can be achieved with low-cost sensing and communication on resource-constrained devices and possibly with collaboration among many different devices.
- E William and MC Chan, SpeedCollect: Data Collection Using Synchronous Transmission for Low-Power Heterogeneous Wireless Sensor Network, EWSN, Dec 22. pdf
- E William and MC Chan, Low-Power Distinct Sum for Wireless Sensor Networks, DCOSS, May 2022. pdf
- Ebram Kamal William, Mun Choon Chan, InDP: In-Network Data Processing for Wireless Sensor Networks, IEEE International Conference on Sensing, Communication and Networking (SECON) Jun 2019. pdf
- M. Mohammad, XiangFa Guo, and Mun Choon Chan, "Codecast: supporting data driven in-network processing for low-power wireless sensor networks," 17th International Conference on Information Processing in Sensor Networks (IPSN '18).
- Mohammad, Mobashir, Raj Joshi, and Mun Choon Chan. "EleTrack: Ultra-Low-Power Retrofitted Monitoring for Elevators." International Conference on Embedded Wireless Systems and Networks (EWSN 2018), Feb 2018.
5G is expected to support a wide variety of users with very diverse requirements. We are looking at how a combination of Software Defined Networking (SDN), Network Virtualization (NV) and cloud computing can be used to meet the requirements of scaling, flexibility and isolation.
- N Lakshmanan, N Budhdev, MS Kang, MC Chan, J Han, A Stealthy Location Identification Attack Exploiting Carrier Aggregation in Cellular Networks, USENIX Security Symposium, August 2021. pdf
- Nishant Budhdev, Mun Choon Chan, Tulika Mitra, “PR3: Power Efficient and Low Latency Baseband Processing for LTE Femtocells,” IEEE International Conference on Computer Communications (INFOCOM), April 2018. pdf
Network Anaomly Detection
This research project focuses on exploiting the availability of enormous amount of customers and traffic data that are generated by telcos. These techniques include analysis of traffic/customer/application data to detect anomalies.
- Q. Nguyen, K. Lim, D. Divakaran, K. Low, MC. Chan, GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection, IEEE Conference on Communications and Network Security (CNS), Jun 2019. pdf