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Algorithmic Models of Wireless Communication

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Title: Algorithmic Models of Wireless Communication


1
Algorithmic Models of Wireless Communication
  • Magnús M. Halldórsson
  • Reykjavik University, Iceland

2
Its Wireless World
GSM
3G
P2P
WiMax
WiFi
? Wireless communication
Ad-hoc
Sensor networks
Mobility
Ambient
Ubiquitous
Pervasive
3
Algorithmic Agenda
  • How to model wireless communication
  • Particularly, interference
  • Capture realism
  • Analytically feasible
  • How to solve fundamental problems
  • Algorithmic strategies
  • Structural properties
  • Modus operandi
  • Ignore constant factors

4
Models of Interference
5
Tradeoffs in Models
6
Models for Interference
  • Two standard models in wireless networking

Protocol Model (graph-based, simpler)
Physical Model (SINR-based, more realistic)
7
CS Models e.g. Disk Model (Protocol Model)
ReceptionRange
InterferenceRange
8
Inductive independence
  • There is a disc that intersects at most 3
    mutually non-overlapping discs
  • Efficient 3-approximate algorithms for
  • Independent set (maximize throughput)
  • Coloring (minimize latency)
  • Weighted independent set (maximize sustained
    throughput)

9
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10
EE Models e.g. SINR Model (Physical Model)
11
(No Transcript)
12
Hard instances for traditional graph-based models
  • One link per slot, in graph-based models
  • Single slot, in physical model (with appropriate
    power control)

13
Signal transmission
  • Radio signal diminishes as it travels
  • In the ideal case, the path loss is proportional
    towhere d distance ? path loss
    constant (usually, 2 lt ? lt 6), depends on medium

14
Affectance
Uniform power
?2
u
2
3.5
5
5
w
 
H, Wattenhofer 09
15
Affectance
Power control
?2
u
2
Pu 1
3.5
5
5
w
Pw 3
H, Wattenhofer 09
16
Affectance
?2
v
u
3
3
4
4
3
w
17
Core problems of wireless scheduling
  • Given A set of communication links
  • Capacity problem Find the maximum size feasible
    subset of links

18
Core problems of wireless scheduling
  • Given A set of communication links
  • Capacity problem Find the maximum size feasible
    subset of links
  • Scheduling problem
  • Partition the links into fewest possible slots

19
The job of the MAC layer
  • MAC Media Access Control
  • The nodes in a wireless network communicate over
    a shared resource the spectrum
  • The task of the MAC layer is to coordinate access
    to the spectrum
  • Who gets to talk when

20
Results on Capacity and Scheduling
  • Capacity has constant-factor approximations for
  • Uniform power in R2, with ?gt2.
    Goussevskaia,H,Wattenhofer,Welzl09
  • Any (reasonable) fixed power in general metrics
    H, Mitra, SODA11
  • Arbitrary power control Kesselheim, SODA11
  • Also, more recently, with power limitations
    Wan12, Kesselheim12
  • Uniform power with spectrum sharing (cognitive
    radio) H,Mitra12
  • Fixed power with variable data rates
    Kesselheim12
  • Uniform power with a distributed learning
    algorithm Asgeirsson, Mitra 11
  • Scheduling has constant-factor approximation for
  • Linear power Fanghanel,Kesselheim,Vöcking09
    Tonoyan11
  • Equal-length links Goussevskaia,Oswald,Wattenhofe
    r, 07 H 09

21
Weighted inductiveness
Weighted degree of v
  • A link lv in a set S is t-good if av(S)aS(v)
    t.
  • A set of links is is t-inductive independent
    if any subset contains a t-good link
  • H, Holzer, Mitra, Wattenhofer, SODA13 Any
    set of links in any metric is O(1)-inductive
    independent, except possibly when using uniform
    power.
  • Applications
  • Capacity algorithms
  • (Multi-hop) distributed scheduling
  • Connectivity
  • Spectrum sharing auctions Hoefer, Kesselheim,
    Vöcking 11,12
  • Dynamic packet scheduling

Kesselheim, Vöcking, DISC10
22
Experimental Work
23
Experimental Work
Putting theory to the test
24
Testbed experimentation
25
Experimental Group
  • Students

Ýmir Vigfússon
Helga Guðmundsóttir
Henning Úlfarsson
Sveinn Fannar Kristjánsson
Eyjólfur Ingi Ásgeirsson
Axel Guðmundsson
Sindri Magnússon
Joe Foley
26
Theory Group
  • Pradipta Mitra, post-doc
  • Marijke Bodlaender, Ph.D. student
  • Hörður Ingi Björnsson, M.S. student
  • Eyjólfur
  • Magnús

Henning
27
Other Collaborators
  • Sverrir Ólafsson, prófessor, Reykjavik University
  • Previously at British Telecom
  • Roger Wattenhofer, prófessor, ETH Zurich
  • Berthold Vöcking, prófessor, TU Aachen

28
Questions?
Thank you
Post-doc Ph.D. positions available
Slides Thanks to Wattenhofer Lab, ETH
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