Lili Qiu

R3: Resilient Routing Reconfiguration

Ye Wang, Hao Wang, Ajay Mahimkar, Richard Alimi, Yin Zhang, Lili Qiu, and Yang Richard Yang
Appears in: 
CCR October 2010

Network resiliency is crucial to IP network operations. Existing techniques to recover from one or a series of failures do not offer performance predictability and may cause serious congestion.

Spatio-Temporal Compressive Sensing and Internet Traffic Matrices

Yin Zhang, Matthew Roughan, Walter Willinger, and Lili Qiu
Appears in: 
CCR October 2009

Many basic network engineering tasks (e.g., traffic engineering, capacity planning, anomaly detection) rely heavily on the availability and accuracy of traffic matrices. However, in practice it is challenging to reliably measure traffic matrices. Missing values are common. This observation brings us into the realm of compressive sensing, a generic technique for dealing with missing values that exploits the presence of structure and redundancy in many realworld systems.

Predictable Performance Optimization for Wireless Networks

Yi Li, Lili Qiu, Yin Zhang, Ratul Mahajan, and Eric Rozner
Appears in: 
CCR October 2008

We present a novel approach to optimize the performance of IEEE 802.11-based multi-hop wireless networks. A unique feature of our approach is that it enables an accurate prediction of the resulting throughput of individual flows. At its heart lies a simple yet realistic model of the network that captures interference, traffic, and MAC-induced dependencies. Unless properly accounted for, these dependencies lead to unpredictable behaviors. For instance, we show that even a simple network of two links with one flow is vulnerable to severe performance degradation.

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