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Mobile Agents for Adaptive Routing. Presented by Hong-Jiun Chen & Manu Prasanna. Gianni Di Caro & Marco Dorigo. Hong-Jiun. Manu. Outline. Introduction Overview of Routing Algorithms Communication Network Model AntNet Other Routing Algorithms

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mobile agents for adaptive routing
Mobile Agents for Adaptive Routing

Presented by Hong-Jiun Chen

& Manu Prasanna

Gianni Di Caro & Marco Dorigo

outline

Hong-Jiun

Manu

Outline
  • Introduction
  • Overview of Routing Algorithms
  • Communication Network Model
  • AntNet
  • Other Routing Algorithms
  • Experiment Settings
  • Experiment Results
  • Conclusion
introduction

Real ants have been shown to be able to find the shortest paths by using only the pheromone trail deposited by other ants

I’m Real Ant

Introduction
  • AntNet
introduction1
Introduction
  • AntNet
  • A new routing algorithm for telecommunication networks
  • An adaptive, distributed, mobile-agents-based algorithm
  • Apply it in a datagram network
introduction2
Introduction
  • Terminology
  • Routing
  • Throughput
  • Delay (Latency)
introduction3
Introduction
  • Routing
  • It refers to the activity of building forwarding tables, one for each node in the network, which tell incoming data which link to use to continue their travel towards the destination node.
introduction4
Introduction
  • Throughput
  • It is the number of bits which the network is able to carry in a given period of time
introduction5
Introduction
  • Delay (latency)
  • Propagation delay
  • Queuing delay
  • Processing delay
  • Transmission delay: The time elapsed from the moment the first bit of the message is transmitted till the last bit of the message is transmitted
outline1
Outline
  • Introduction
  • Overview of Routing Algorithms
  • Communication Network Model
  • AntNet
  • Other Routing Algorithms
  • Experiment Settings
  • Experiment Results
  • Conclusion
routing algorithm
Routing Algorithm
  • Goal
  • To direct traffic from sources to destinations
  • Network performance 
  • Costs
routing algorithm1
Routing Algorithm
  • The performance metrics:
    • throughput (bits/second)
    • delay (second)
  • Static or Adaptive?
outline2
Outline
  • Introduction
  • Overview of Routing Algorithms
  • Communication Network Model
  • AntNet
  • Other Routing Algorithms
  • Experiment Settings
  • Experiment Results
  • Conclusion
communication network model
Communication Network Model
  • Apply on datagram networks without concerning congestion and admission control
  • FIFO
  • When links resources are available, they are reserved and the transfer is set up
  • The time it takes a packet from one node to another depends on its size and the link transmission characteristics
  • No ACK
outline3
Outline
  • Introduction
  • Overview of Routing Algorithms
  • Communication Network Model
  • AntNet
  • Other Routing Algorithms
  • Experiment Settings
  • Experiment Results
  • Conclusion
antnet

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I’m Forward Ant

AntNet
  • 1. Forward antFsd is launched

Describe it by 6 simple steps:

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  • 2. Ssd (k) is inserted, time elapsed is stored in stack

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  • 2.keep it going to next hop

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  • 3.A circle is detected

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  • 3.A circle detected, delete all the nodes in that circle from the stack

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  • 3. Start over from the last node without circles

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  • 4. Destination node reached

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I’m Backward Ant

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  • 4. Destination node reached, the ant Fsd generates another backward antBds

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  • 5. Backward ant pops its stack to know the next hop node

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  • 5. Backward ant pops its stack to know the next hop node

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  • 5. Backward ant pops its stack to know the next hop node

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AntNet
  • 5. Backward ant pops its stack to know the next hop node

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  • 6. Whenever the Backward ant arrives a node, it updates 2 things:
  • 1. A List Trip(i , i2)
  • 2. The Routing Table

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  • 1. Change A List Trip(i , i2)
  • It estimates arithmetic mean values i and associated variances i2 for trip times from the node itself to all the nodes i in the network

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  • 2. Change The Routing Table

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outline4

Manu

Outline
  • Introduction
  • Overview of Routing Algorithms
  • Communication Network Model
  • AntNet
  • Other Routing Algorithms
  • Experiment Settings
  • Experiment Results
  • Conclusion
outline5
Outline
  • Introduction
  • Overview of Routing Algorithms
  • Communication Network Model
  • AntNet
  • Other Routing Algorithms
  • Experiment Settings
  • Experiment Results
  • Conclusion
experimental settings
Experimental Settings
  • Topology and Physical properties
  • NFSNET with 14 nodes and 21 links
  • Bandwidth of links = 1.5Mbit/s
  • Link/node fault probability = 0
  • Local buffer capacity = 1GB
  • Statistical multiplexing
experimental settings1
Experimental Settings
  • Traffic Patterns
  • Static Model
        • Constant bit rate
  • Dynamic Model
        • Variable bit rate
experimental settings2
Experimental Settings
  • Geographical Distribution of Traffic
  • Uniform-deterministic distribution
  • Uniform-random distribution
  • Uniform-deterministic-hot-spots
  • Uniform-random-hot-spots
outline6
Outline
  • Introduction
  • Overview of Routing Algorithms
  • Communication Network Model
  • AntNet
  • Other Routing Algorithms
  • Experiment Settings
  • Experiment Results
  • Conclusion
experimental results
Experimental Results
  • Performance of all algorithms near optimal for low and uniform traffic loads
  • AntNet especially good in CBR case
  • AntNet algorithm shows overall best performance
  • Daemon algorithm (used for comparisons)
outline7
Outline
  • Introduction
  • Overview of Routing Algorithms
  • Communication Network Model
  • AntNet
  • Other Routing Algorithms
  • Experiment Settings
  • Experiment Results
  • Conclusion
conclusion
Conclusion
  • AntNet shows a robust behavior
  • Reaction time of algorithm is acceptable
  • Impact on network resources is neglectable
strengths and possible weaknesses
Strengths

Possible Weaknesses

Strengths and Possible Weaknesses
  • Good idea
  • Nice buildup
  • Time tested idea (ants have been around for sometime… 80 million years)
  • Scalability issues are ignored
  • Setup costs and time?
  • Feasibility for wireless networks?
new ideas
New Ideas
  • The term is defined in the Oxford English Dictionary as The process by which the results of an insects activity act as a stimulus to further activity, and is used in the mobile robotics literature to describe activity in which an agent supplies changes to the world architecting its future behavior, usually in a useful way

AntNet: new algorithm for adaptive routing

  • Stigmergy
relevance to ies
Relevance to IES
  • If the goal of AI/Robotics is to make machines as intelligent as humans we should first start with imitating lesser intelligent animals (eg: ants)
  • Social behavior, community behavior, cooperation among ants/bees can be applied easily in robotics
the ants a community of microrobots
The Ants: A Community of Microrobots
  • Source: MIT Artificial Intelligence Lab
  • Goals
    • push the limits of microrobotics by integrating many sensors and actuators into a small package
    • form a structured robotic community from the interactions of many simple individuals
the ants a community of microrobots1
The Ants: A Community of Microrobots
  • Community behavior:
    • Clustering around food
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