My research interests generally include software defined networking and distributed machine learning, with a focus on scalability issues. I’m interested in both designing theoretical algorithms, and in developing practical systems that are deployable in the real Internet.
Efficient Network Update for Software Defineed Networking
Our research group has been developing technologies to improve the efficiency of network update for SDN.Selected Publications
- “Efficient and Consistent TCAM Updates,” in Proc. IEEE INFOCOM 2020, Jul. 2020
- “RuleTailor: Optimizing Flow Table Updates in OpenFlow Switches with Rule Transformations,” IEEE Transactions on Network and Service Management, Vol. 16(4):1581-1594, Dec. 2019.
- “FastRule: Efficient Flow Entry Updates for TCAM-Based OpenFlow Switches,” IEEE Journal on Selected Areas in Communications, Vol. 37(3):484-498, Mar. 2019.
- “Efficient Recovery Path Computation for Fast Reroute in Large-scale Software Defined Networks,” IEEE Journal on Selected Areas in Communications, Vol. 37(8):1755-1768, Aug. 2019.
NF Placement
Selected Publications
- “FlexChain: Bridging Parallelism and Placement for Service Function Chains,” IEEE Transactions on Network and Service Management, Vol. 18(1):195-208, Mar. 2021
- “DDQP: A Double Deep Q-Learning Approach to Online Fault-tolerant SFC Placement,” IEEE Transactions on Network and Service Management, Vol. 18(1):118-132, Mar. 2021
- “Energy-Efficient and Interference-Aware VNF Placement with Deep Reinforcement Learning,” in Proc. IFIP Networking 2021
Programmable Data Plane
Selected Publications
- “P4Neighbor: Efficient Link Failure Recovery with Programmable Switches,” IEEE Transactions on Network and Service Management, Vol. 18(1):388-401, Mar. 2021
- “P4SFC: Service Function Chain Offloading with Programmable Switches,” in Proc. IEEE IPCCC 2020, short paper, Nov. 2020, Austin, Texas, USA