Toronto Networking Seminar


Organized by Department of Computer Science and
Department of Electrical and Computer Engineering, University of Toronto







Special Session on Samples 
from INFOCOM'10




  A special session of the 
  Toronto Networking Seminar will be held this week. Members of the University 
  of Toronto will present a sampling of their papers published in INFOCOM'10.

  

  Time: 2 pm, Friday, March 26

  Location: BAB025 (Bahen Centre Basement)

  

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  Talk #1: 

  

  Compressive Sensing Based Positioning Using RSS of WLAN Access Points

  

  Presented by Ms. Chen Feng

  

  The sparse nature of location finding problem makes the theory of compressive 
  sensing desirable for indoor positioning in Wireless Local Area Networks (WLANs). 
  In this paper, we address the received signal strength (RSS)-based 
  localization problem in WLANs using the theory of compressive sensing (CS), 
  which offers accurate recovery of sparse signals from a small number of 
  measurements by solving an 1-minimization problem. A pre-processing procedure 
  of orthogonalization is used to induce incoherence needed in the CS theory. In 
  order to mitigate the effects of RSS variations due to channel impediments, 
  the proposed positioning system consists of two steps: coarse localization by 
  exploiting affinity propagation, and fine localization by the CS theory. In 
  the fine localization stage, access point selection problem is studied to 
  further increase the accuracy. We implement the positioning system on a WiFi-integrated 
  mobile device (HP iPAQ hx4700 with Windows Mobile 2003 Pocket PC) to evaluate 
  the performance. Experimental results indicate that the proposed system leads 
  to substantial improvements on localization accuracy and complexity over the 
  widely used traditional fingerprinting methods.

  

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  Talk #2:

  

  Optimal Control of Constrained Cognitive Radio Networks with Dynamic 
  Population Size

  

  Presented by Dr. Mahdi Lotfinezhad

  

  We consider the problem of optimal control for throughput utility maximization 
  in cognitive radio networks with dynamic user arrivals and departures. The 
  cognitive radio network considered in this work consists of a number of 
  heterogeneous sub-networks. These sub-networks may be power-constrained and 
  are required to operate in such a way that the average total interference 
  received on primary channels are kept below given thresholds. We develop a 
  control policy that performs joint admission control and resource scheduling. 
  Through Lyapunov optimization techniques, we show that the proposed policy 
  achieves a utility performance within $O(\delta)$ of optimality for any 
  positive $\delta$. We further show that this arbitrarily closeness to 
  optimality comes at the price of having a delay that is $O(\frac{1}{\delta})$ 
  in admitting users. We also propose constant factor approximations of the 
  policy for distributed implementation.

  

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  Talk #3:

  

  UUSee: Large-Scale Operational On-Demand Streaming with Random Network Coding

  

  Presented by Prof. Baochun Li

  

  In this talk, we present the objectives, rationale, and design in the first 
  production deployment of random network coding, where it has been used in the 
  past year as the cornerstone of a large-scale production on-demand streaming 
  system, operated by UUSee Inc., delivering thousands of on-demand video 
  channels to millions of unique visitors each month. To achieve a thorough 
  understanding of the performance of network coding, we have collected 200 
  Gigabytes worth of real-world traces throughout the 17-day Summer Olympic 
  Games in August 2008, and present our lessons learned after an in-depth 
  trace-driven analysis.