OLSRp: Predicting Control Information to Achieve Scalability in OLSR Ad Hoc Networks - PowerPoint PPT Presentation

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OLSRp: Predicting Control Information to Achieve Scalability in OLSR Ad Hoc Networks

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Title: Slides INTERACT-9 Author: Carlos Molina Last modified by: CMC Created Date: 6/17/1995 11:31:02 PM Document presentation format: Presentaci n en pantalla – PowerPoint PPT presentation

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Title: OLSRp: Predicting Control Information to Achieve Scalability in OLSR Ad Hoc Networks


1
OLSRp Predicting Control Information to Achieve
Scalability in OLSR Ad Hoc Networks
Santander (SPAIN) - September 22-24, 2010
  • Esunly Medina ?
  • Roc Meseguer ?
  • Carlos Molina ?
  • Dolors Royo ?

? Dept. Arquitectura de Computadors Universitat
Politècnica de Catalunya Barcelona, Spain
esunlyma, meseguer, dolors_at_ac.upc.edu
? Dept. Enginyeria Informàtica i
Matemàtiques Universitat Rovira i
Virgili Tarragona, Spaincarlos.molina_at_urv.net
2
OLSR
Outline
  • Motivation
  • Potentiality
  • OLSRp
  • Conclusions Future Work

3
Motivation
4
Motivation
  • Ad-hoc networks
  • Need for maintaining network topology
  • Control messages consume network resources
  • Proactive link state routing protocols
  • Each node has a topology map
  • Periodically broadcast routing information to
    neighbors

but when the number of nodes is high
5
can overload the network!!!
6
OLSR
OLSR Control Traffic and Energy
  • OLSR is one of the
  • most intensive
  • energy-consumers

Traffic and energy do NOT scale !!!
7
can we increase scalability of routing
protocols for ad-hoc networks?
8
OLSR
DQ principle
  • Data per query Queries per second ?constant
  • For routing protocols
  • D Size of packets
  • Q Number of packets per second sent to the
    network
  • We focus on Q
  • Reducing transmitted packets
  • Without adding complexity to network management
  • HOW?

PREDICTING MESSAGES !!!!
9
We propose a mechanism for increasing
scalability of ad-hoc networks based on link
state proactive routing protocols
  • Called OLSRp
  • Predicts duplicated topology-update messages
  • Reduce messages transmitted through the network
  • Saves computational processing and energy
  • Independent of the OLSR configuration
  • Self-adapts to network changes.

10
Potentiality
11
OLSR
Experimental Setup
  • NS-2 NS-3
  • Grid topology, D 100, 200, 500 m
  • 802.11b Wi-Fi cards, Tx rate 1Mbps
  • Node mobility
  • Static, 0.1, 1, 5, 10 m/s
  • Friis Propagation Model
  • ICMP traffic
  • OLSR control messages

12
OLSR
OLSR Messages distribution
  • TC vs HELLO

Ratio of TC messages is significant for low
density of nodes
13
OLSR
Control Information Repetition
Number of nodes does not affect repetition
14
OLSR
Control Information Repetition
Density of nodes slightly affects repetition
15
OLSR
Control Information Repetition
Repetition is mainly affected by mobility
16
OLSR
Control Information Repetition
Repetition still being significant for high node
speeds
17
OLSRp
18
OLSR
OLSRp Basis
  • Prevent MPRs from transmitting duplicated TC
    throughout the network
  • Last-value predictor placed in every node of the
    network
  • MPRs predicts when they have a new TC to transmit
  • The other network nodes predict and reuse the
    same TC
  • 100 accuracy
  • If predicted TC ? new TC ? MPR sends the new TC
  • HELLO messages for validation
  • The topology have changed and the new TC must be
    sent
  • The MPR is inactive and we must deactivate the
    predictor

19
OLSR
OLSRp Layers
TCWifi ? TCOLSR
if MPR TCOLSR ? TCWifi
if (TCnTCn-1) TCOLSRp ? TCOLSR else TCWifi
?TCOLSR
if MPR? if(TCnTCn-1) TCOLSRp else TCOLSR ?
TCWifi
20
OLSR
OLSRp Basis
  • Each node keeps a table whose dimensions depends
    on the number of nodes
  • Each entry records info about a specific node
  • The nodes _at_IP
  • The list of _at_IP of the MPRs (O.A.) that announce
    the node in their TCs and the current state of
    the node (A or I). (HELLO messages received).
  • A predictor state indicator for MPR nodes (On or
    Off)
  • On when at least one of the TC that contains
    information about the MPR is active
  • Off when the node is inactive in all the
    announcing TC messages (new TC message will be
    sent)

21
OLSR
OLSRp Example
B
B
22
OLSR
OLSRp Example
B
B
NODE D TABLE
23
OLSR
OLSRp Example
X
B
B
NODE D TABLE
24
OLSR
OLSRp Example
X
B
B
NODE D TABLE
25
OLSR
OLSRp Example
X
B
B
NODE D TABLE
26
OLSR
OLSRp Benefits
  • Reduction in
  • Control traffic

27
OLSR
OLSRp Some Results
28
Conclusions Future Work
29
OLSR
Conclusions Future Work
  • Conclusions
  • OLSRp has similar performance than standard OLSR
  • Can dynamically self-adapt to topology changes
  • Reduces network congestion
  • Saves computer processing and energy consumption
  • Future Work
  • Further evaluation of OLSRp performance
  • Assessment in real-world testbeds
  • Application in other routing protocols

30
Questions?
Santander (SPAIN) - September 22-24, 2010
OLSRp Predicting Control Information to Achieve
Scalability in OLSR Ad Hoc Networks
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