AntNet: A nature inspired routing algorithm 1 Lecturer: Nona Helmi Student:

AntNet:A nature inspired routing

algorithm

1

Lecturer: Nona Helmi

Student:

Presentation Content

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Introduction

Rapid growth of networks Increase of network communication

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What Is Routing?

Routing is the act of moving information across a network from a source to a destination.

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Tasks of Routing The tasks of a routing protocol are

determine the optimal paths route information


Design Goals

Optimality Simplicity and low overhead Rapid convergence Robustness and stability Flexibility


Agent & multi-agent system

Agent is a software that have some specification: Autonomy Reactivity Pro-activeness Social ability

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Mobile Agent

A mobile agent is a software agent that can move between locations (mobility).


Nature inspired algorithms

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PSO ABC GA ACO

EndConclusion ReferencesAntNet Algorithmintroduction Routing basics MAS-ACOMAS-ACO

ACO introduced by Marco Dorigo (MILAN,ITALY) in his

doctoral thesis in 1992


M. Dorigo, Optimization, Learning and Natural Algorithms, PhD thesis, Politecnico di Milano, Italie,1992

ACO (cont.)

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Based on ants method of finding food. Using to solve

traveling salesman routing in networks load balancing


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Swarm intelligence


Stigmergy

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A mechanism of indirect coordination between agents .


The process that ants search the shortest path

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(i) (ii) (iii)


Ants & routing

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Ants dropping different pheromones used to compute “shortest” path from source to destination(s);Advantages:

more flexible adaptation to failures and network congestion; use only local knowledge for routing and avoid costly communication of state to all network nodes.

EndConclusion ReferencesAntNet AlgorithmAntNet Algorithmintroduction Routing basics MAS-ACO

AntNet

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AntNet: A Mobile agents Approach to Adaptive Routing. Introduced by GIANNI DI CARO and MARCO DORIGO.

G.D Caro and M.Dorigo,“ AntNet: distributed stigmergetic control for communications networks.” Journal of Artificial Intelligence Research 9 (1998), 317-365.

EndConclusion Referencesintroduction Routing basics MAS-ACO AntNet AlgorithmAntNet Algorithm

AntNet:Description Two kinds of Agents (Ant Packets)

Forward Ant. explores the network and collects

information. when reaches the destination,

changes into backward ant.Backward Ant.

goes back in the same path as forward ant.

update routing tables for all the

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AntNet:Description (cont.)

Two data structures stored in each network node:

Routing table (P)

An array

NjwMjbestjji ..1,),,( 2

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mean

variancethe best trip time from i to j.


AntNet:Description (cont.)

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Outgoing Links Routing table

Local traffic statistics

Network Node(i)

P11 P12 P1N

P2N

PmN,

P21 P21

Pm1 Pm2

.......

.......

Network Nodes

),,(1

211 bestw ),,(

2

222 bestw ),,( 2

NbestNN w


AntNet algorithm At regular interval δt,a forward agent is launched from

source toward the destination. At each node,the agent keeps the memory of the path

and the traffic condition. At each node, the next hop is selected from among all

those neighboring nodes which have not yet been visited.

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)1|(|1

k

nndnd N

lPP


AntNet algorithm (cont.)

If a cycle is detected, the ant memory is popped out of stack.

When reaches destination, it generates a backward ant, transfers its stack to it and dies.

Backward ant takes the same path back using the ant stack transferred by the forward ant.

When a backward ant reaches a node k, Mk and Routing table for destination d is updated.


AntNet algorithm (cont.)

Pfd = Pfd + r(1- Pfd ) Pnd = Pnd - r Pnd , n Nk, n f


AntNet: Overview

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13

4

2

5

6

Forward Ant (13)

Backward Ant (13)

At Node 2, Update Routing Information for 3

At Node 1, Update Routing Information for 3 and Update routing information for 2


Conclusion

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The main characteristics of AntNet algorithm Nature inspired, Adaptivity Inherent parallelism Sclalablity

the Ant Colony Optimization can be applied to many other hard problems.

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References

1. B.Baran ,R.Sosa, AntNet routing algorithm for data networks based on mobile agents” Inteligencia Artificial’ (2001),75-84.

2. Dorigo M., Di Caro G.A., Gambardella L.M., "Ant Algorithms for Discrete Optimization" , Artificial Life, Vol. 5, N. 2, 1999

3. Dorigo M., Stuetzle T., Ant Colony Optimization, scholarpedia, 2010

4. Di Caro G. A. "Ant Colony Optimization and its application to adaptive routing in telecommunication networks" PhD thesis in Applied Sciences, Polytechnic School, Université Libre de Bruxelles, Brussels, Belgium, 2004

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Questions, Comments?

Thank You

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AntNet: A nature inspired routing algorithm 1 Lecturer: Nona Helmi Student: