research
∙
04/24/2020
CFR-RL: Traffic Engineering with Reinforcement Learning in SDN
Traditional Traffic Engineering (TE) solutions can achieve the optimal o...
share
research
∙
01/22/2020
To schedule or not to schedule: when no-scheduling can beat the best-known flow scheduling algorithm in datacenter networks
Conventional wisdom for minimizing the average flow completion time (AFC...
research
∙
12/31/2019
SharpEdge: An Asynchronous and Core-Agnostic Solution to Guarantee Bounded-Delays
What are the key properties that a network should have to provide bounde...
research
∙
12/26/2019
Make TCP Great (again?!) in Cellular Networks: A Deep Reinforcement Learning Approach
Can we instead of designing just another new TCP, design a TCP plug-in w...
research
∙
08/02/2019
Bounding Queue Delay in Cellular Networks to Support Ultra-Low Latency Applications
Most of the current active queue management (AQM) designs have major iss...
research
∙
06/14/2019
Intelligent Anomaly Detection and Mitigation in Data Centers
Data centers play a key role in today's Internet. Cloud applications are...
research
∙
05/13/2019
Enabling Mobility in LTE-Compatible Mobile-edge Computing with Programmable Switches
Network softwarization triggered a new wave of innovation in modern netw...
research
∙
11/24/2018
In-network Congestion-aware Load Balancing at Transport Layer
Load balancing at transport layer is an important function in data cente...
research
∙
10/29/2018
C2TCP: A Flexible Cellular TCP to Meet Stringent Delay Requirements
Since current widely available network protocols/systems are mainly thro...
research
∙
07/18/2018
HyLine: a Simple and Practical Flow Scheduling for Commodity Datacenters
Today's datacenter networks (DCNs) have been built upon multipath topolo...
research
∙
07/07/2018
Cellular Controlled Delay TCP (C2TCP)
Cellular networks have special characteristics including highly variable...
research
∙
06/21/2018