Ranveer Chandra

White Space Networking with Wi-Fi like Connectivity

Paramvir Bahl, Ranveer Chandra, Thomas Moscibroda, Rohan Murty, and Matt Welsh
Appears in: 
CCR October 2009

Networking over UHF white spaces is fundamentally different from conventional Wi-Fi along three axes: spatial variation, temporal variation, and fragmentation of the UHF spectrum. Each of these differences gives rise to new challenges for implementing a wireless network in this band. We present the design and implementation of WhiteFi, the firstWi-Fi like system constructed on top of UHF white spaces. WhiteFi incorporates a new adaptive spectrum assignment algorithm to handle spectrum variation and fragmentation, and proposes a low overhead protocol to handle temporal variation.

A Case for Adapting Channel Width in Wireless Networks

Ranveer Chandra, Ratul Mahajan, Thomas Moscibroda, Ramya Raghavendra, and Paramvir Bahl
Appears in: 
CCR October 2008

We study a fundamental yet under-explored facet in wireless communication – the width of the spectrum over which transmitters spread their signals, or the channel width. Through detailed measurements in controlled and live environments, and using only commodity 802.11 hardware, we first quantify the impact of channel width on throughput, range, and power consumption. Taken together, our findings make a strong case for wireless systems that adapt channel width. Such adaptation brings unique benefits.

Towards Highly reliable Enterprise Network Services via Inference of Multi-level Dependencies

Paramvir Bahl, Ranveer Chandra, Albert Greenberg, Srikanth Kandula, David A. Maltz, and Ming Zhang
Appears in: 
CCR October 2007

Localizing the sources of performance problems in large enterprise networks is extremely challenging. Dependencies are numerous, complex and inherently multi-level, spanning hardware and software components across the network and the computing infrastructure. To exploit these dependencies for fast, accurate problem localization, we introduce an Inference Graph model, which is welladapted to user-perceptible problems rooted in conditions giving rise to both partial service degradation and hard faults.

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