Documents/PEL

About the Princeton EDGE Lab

Strategic_Plan

Publication: 2013-12-23

Source: http://scenic.princeton.edu/about.php

Theory is "inalienable" since it offers explanatory, rather than descriptive models and top-down design with predictive power. Theory is also "incomplete" given its sensitivity to the mathematical crystallization and the need to make a difference in live networks. As an edge between theory and practice of networking, the Princeton EDGE Lab builds systems designed by proven theorems, and proves theorems about deployed systems.

It targets: 1. Bigger overlap between the two (e.g., develop the theory for tight bounds on convergence rate, transient behavior characterization rather than equilibrium behavior, impact of control parameter granularity and feedback noise, remove timescale separation assumptions, etc.) 2. New theory questions (e.g., proper accounting of computational and communication overhead, or simplicity-driven optimization: insist on zero overhead rather than optimality proof and then tightly bound suboptimality gap and its impact on user performance) 3. Theory-inspired deployment (e.g., transfer some of the theory inspired algorithms to commercial adoption and large scale operations serving real customers, and turn some of the challenges in that process to inspire new theory).

Organization:

Name:Princeton EDGE Lab

Acronym:PEL

Description:
The lab consists of two rooms and has experimental facilities to provide an edge between the "theory node" and the "systems node" in the networking research community, especially for edge networking. It leverages the lessons and data accumulated through realistic experiments to validate the predictions of theory, falsify the assumptions behind theory, sharpen the characterizations that are loose in theory, and inspire new question formulations in theory. It partners with many systems and deployments in both academia and industry. It builds systems designed by proven theorems, and proves theorems about deployed systems.

Stakeholder(s):

  • Mung Chiang: Professor of Electrical Engineering; Director of EDGE Lab -- Mung Chiang is the Arthur LeGrand Doty Professor of Electrical Engineering at Princeton University. He is also an affiliated faculty in Applied and Computational Mathematics, and in Computer Science, and has served as the Director of Graduate Studies in Electrical Engineering since 2009. He received his B.S. (Hons.), M.S., and Ph.D. degrees from Stanford University in 1999, 2000, and 2003, respectively, and was an Assistant Professor 2003-2008, a tenured Associate Professor 2008-2011, and a Professor 2011-2013 at Princeton University. He was a Hertz Fellow in 1999-2003, a H. B. Wentz Junior Faculty at Princeton in 2005, and was elected an IEEE Fellow in 2012. Chiang's research areas include the Internet, wireless networks, broadband access networks, content distribution networks, network economics, and online social networks...

  • Bharath Balasubramanian: Postdoctoral research associate

  • Zhenming Liu: Postdoctoral research associate

  • Aveek Dutta: Postdoctoral research associate

  • Felix Ming Fai Wong: PhD candidate

  • Jiasi Chen: PhD candidate

  • Srinivas Naryana: PhD candidate; Co-advised by Jennifer Rexford

  • Chris Brinton: PhD candidate

  • Carlee Joe-Wong: PhD candidate

  • Michael Wang: PhD candidate

  • Shirley Xiaoli Wang: PhD student

  • Princeton EDGE Lab Sponsors

  • National Science Foundation

  • Office of Naval Research

  • Air Force Office of Sponsored Research

  • Army Research Office

  • Princeton University

  • DARPA

  • Nokia-Siemens

  • Qualcomm

  • AT&T

  • Microsoft: University Research Program: The EDGE Lab

  • Google

  • Telcordia

  • Intel

  • HP

  • SES

Content
Visions
Missions
Values
1: Engineering Artifacts in Networking