Illinois Center forWireless Systems

Wireless Networks: Algorithms and Optimization

R. SrikantECE/CSL

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Researchers & Selected TopicsTopics

Tamer BasarChris Hadjicostis

Bruce HajekJennifer HouP. R. KumarSean Meyn

R. S. SreenivasR. Srikant

Mathematical Tools

Cross-layer design Optimization

Power Control Distributed Algorithms

Distributed MAC Information Theory

Multi-channel, multi-antenna protocols

Game Theory

Performance Analysis

Systems & Control

Security Stochastic Processes

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Technical Approach

Establish fundamental limits of performance of single-hop

and multi-hop wireless networks

Translate algorithms into practical protocols for

wireless networks accounting for overhead, complexity

Design distributed algorithms to achieve or approximate the

above performance limits

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Example Project: Clean-Slate Design

Sponsor: NSF Organizations: UIUC, Princeton, Texas-Austin,

Purdue, Ohio State Goal: Clean-state design of wireless networks

Is there an optimal network architecture? Should it be layer separated (PHY, MAC, network, transport, etc.) or cross-layered?

Are there near-optimal architectures that tradeoff between efficiency, robustness, signaling overhead, complexity, etc.?

Develop methodologies to evaluate alternativesKey difficulty: No notion of a reliable bit-pipe

between a pair of nodes

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Example Project: From Theory to Practice

Sponsor: DARPA Companies: Lockheed-Martin, Alcatel-Lucent Universities: UIUC, Stanford, Princeton, UCSB Pose the problem of fair, efficient resource

allocation as a convex optimization problemObtain a solution using dual decomposition theoryFind approximate solutions to optimal routing, power

control and MAC algorithmsDevise low-overhead signalling protocol to enable

implementation of approximately optimal algorithms Implement in a 30-50 node MANET

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Example Project: Security & Trustworthiness

Sponsor: Motorola Organizations: UIUC Design algorithms for identifying and isolating

misbehaving users in multi-hop wireless networks and devise incentive mechanisms to encourage cooperative behaviorAlgorithms have to be distributedNo single user should have an incentive to deviate

from socially responsible behaviorRobust to coalitionsLow overhead

Recent Results: Optimal Architecture

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What does it mean to “optimally” allocate resources?

Unlike TCP, source does not react to end-to-end congestion; instead hop-by-hop congestion control

Congestion Control for Flow f : Decrease queue length if ingress queue length is small

Ingress

Queue length

20 60 80 20Weights=Backpressures

-40 -20 60

Cross-layer solution is optimal: power, time slots, routing are all allocated at the same time scale

On the other hand, layering is beneficial for proliferation: can minimal coupling of functionality among layers reap most of the performance benefits?

Optimal Solution

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Recent Results: Scheduling & QoS

Problem: Given QoS constraints on the packet delay at the router, what is the optimal scheduling policy?

Scheduling policy can use queue length, delay of HoL packet, channel conditions in making a decision

Key Result

Using queue-length or head-of-line packet delay information can dramatically improve performance

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QLB: Queue-length based scheduling policy

Greedy: Schedule the user with the best channel

Number of users

Netw

ork

Th

rou

ghp

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Recent Results: Enforcing Cooperation

Problem: Detect misbehaving nodes and provide incentives for all nodes to act in a socially responsible manner

Detecting misbehavior is difficult in wireless networks

Example:C asks D to send a packet to EWhen D transmits to E, B transmits to AD E transmission is successful, but C does not

know

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A B C D E

Game-Theoretic Solution

DARWIN: Distributed, Adaptive Reputation mechanism for WIreless Networks Collect each node’s reputation

based on its forwarding behavior; errors will occur occasionally

Punishment for misbehavior: Tit-for-tat strategy

Accounting for errors: Be contrite (accept punishments assuming that they are due to error)

Above behavior is optimal from a game-theoretic point-of-view: deviation from cooperation is not fruitful

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Can be incorporated into 802.11 or other protocols

Overhead is fixed, independent of network load

Summary

Design of optimal architectures and algorithms for wireless networks

Develop new theory and translate it into practice

Theory-driven protocol stack design can lead dramatic gains in network performance

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