Simulation of Ant Routing Protocol for Adhoc networks in NS2

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Simulation of Ant Routing Protocol for Ad-hoc
networks in NS-2

• MSc thesis presentation

FJ Arbona Bernat E-mail .tudelft.nl
Supervisor prof.dr.ir. P.F.A. Van
Mieghem Mentor ir. S.S. Dhillon Advisor
dr.ir. F.A. Kuipers
November 22, 2006
Faculty of Electrical Engineering, Mathematics
and Computer Science Network Architectures and
Services Group
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Table of Contents

• Introduction
• W_AntNet
• Implementation details
• Algorithm basic description
• Simulation results
• Static scenario
• Mobile scenario
• Larger scenario
• Conclusions and Future Work

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Introduction MANETs (1)

• Mobile ad-hoc networks (MANETs) are increasing in
  popularity.
• Possible applications
• Networks amongst defense and civil security staff
  and their communication devices.
• Traffic and mobility applications.
• Domotica and residential networks.
• Robotics and sensor networks.

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Introduction MANETs (2)

• Routing protocols should resolve
• Lack of fixed infrastructure.
• Dynamic topologies. Multi-hop.
• Bandwidth-constrained.
• Energy-constrained operation.
• Security issues.
• Need for scalabability.

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Introduction ant routing (1)

• Ant routing is a scheme for routing inspired by
  the behavior of real ants
• Ants (control packets) collect information about
  the network conditions and are used to update and
  maintain routing tables.
• Based on swarm intelligence, used to solve
  complex optimization problems.

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Introduction ant routing (2)

• How it works

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Introduction ant routing (3)

• How it works

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Introduction ant routing (4)

• How it works

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Introduction ant routing (5)

• How it works

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Table of Contents

• Introduction
• W_AntNet
• Implementation details
• Algorithm basic description
• Simulation results
• Static scenario
• Mobile scenario
• Larger scenario
• Conclusions and Future Work

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W_AntNetImplementation details

• This project involves simulating ant routing
  protocol for MANETs and comparing its performance
  with other protocols, like AODV or DSR.
• Protocol implemented W_AntNet
• Derived from AntNet.
• Neighbor management added.
• Simulation environment NS-2

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W_AntNetAlgorithm basic description

• FAs are generated regularly at every node.
• Each FA
• Stores address and arrival time of visited nodes.
• Chooses next hop. Cycle detection.
• Once at destination, generates BA.
• Each BA
• Travels same path in opposite direction.
• Updates routing table and local traffic model.
• Neighbor management.

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Table of Contents

• Introduction
• W_AntNet
• Implementation details
• Algorithm basic description
• Simulation results
• Static scenario
• Mobile scenario
• Larger scenario
• Conclusions and Future Work

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Simulation resultsStatic scenario

• 10 nodes manually placed.
• Traffic 9 connections later increased to 15.
• Packet size 64, 128, 512 and 1024 bytes

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Simulation results static scenarioAverage
End-to-End Delay
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Simulation results static scenarioPacket
Delivery Ratio
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Simulation results static scenarioFA sent only
during Training Period
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Simulation results static scenarioFA sent only
during Training Period
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Simulation results static scenarioIntroducing
random loss
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Simulation resultsMobile environment

• 50 mobile nodes in a 1500x300m2 area.
• Mobility
• Speed 1 20 m/s
• 10 pseudorandom scenarios with 7 pausetimes.
• Traffic
• 10, 20 or 30 CBR sources
• Rate 4 pkts/s
• Packet size 64bytes
• Bandwidth radio channel 2Mbps

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Simulation results mobile scenarioAverage
End-to-End Delay
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Simulation results mobile scenarioPacket
Delivery Ratio
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Simulation results mobile scenarioHop-count
optimality
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Simulation results mobile scenarioRouting
overhead
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Simulation results larger scenarioAverage
End-to-End Delay
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Simulation results larger scenarioPacket
Delivery Ratio
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Table of Contents

• Introduction
• W_AntNet
• Implementation details
• Algorithm basic description
• Simulation results
• Static scenario
• Mobile scenario
• Larger scenario
• Conclusions and Future Work

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Conclusions

• High overhead due to route maintenance
• Node queues congested.
• Packets dropped.
• W_AntNet performance is poor compared to AODV or
  DSR.
• FA generation rate is a key parameter.
• Ant routing well suited for fixed networks with
  high capacity channels.

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Future work

• Further simulations using another simulator.
• Try a reactive approach.
• Do some real benchmarks.
• Study energy related issues.

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Any question?

• Thank you very much for your attention!