Mobile Agents for Adaptive Routing Presented by Hong-Jiun Chen & Manu Prasanna Gianni Di Caro & Marco Dorigo

Outline Introduction Overview of Routing Algorithms Communication Network Model AntNet Other Routing Algorithms Experiment Settings Experiment Results Conclusion Hong-Jiun Manu

Introduction AntNet 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 A new routing algorithm for telecommunication networks An adaptive, distributed, mobile-agents- based algorithm Apply it in a datagram network

Introduction Terminology Routing Throughput Delay (Latency)

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.

Introduction Throughput It is the number of bits which the network is able to carry in a given period of time

Introduction Delay (latency) 1. Propagation delay 2. Queuing delay 3. Processing delay 4. 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

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

Routing Algorithm Goal To direct traffic from sources to destinations 1. Network performance  2. Costs 

Routing Algorithm The performance metrics: throughput (bits/second) delay (second) Static or Adaptive?

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

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

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

2 AntNet Describe it by 6 simple steps: A E F C G D S Dest.Prob.NextHop D0.50A D F E A E F G F G A I’m Forward Ant 1. Forward ant F s  d is launched

2 AntNet A E F C G D 1 2. S s  d (k) is inserted, time elapsed is stored in stack S A 0S

2 3 AntNet 2. keep it going to next hop A E F C G D 5A 8C 0S S

AntNet 3. A circle is detected A E F C G D 5A 8C 11E 15F 18C 0S S

AntNet 3. A circle detected, delete all the nodes in that circle from the stack A E F C G D 5A 8 C 11E 15F 18 C 0S S

2 3 AntNet A E F C G D S A 8C 11E 15F 18C 0S OLD 3. Start over from the last node without circles 5A 7G 0S NEW

3 24 AntNet 4. Destination node reached A E F C G D 5A 7G 9D 0S S

1 I’m Backward Ant AntNet 4. Destination node reached, the ant F s  d generates another backward ant B d  s A E F C G D 5A 7G 9D 0S S

1 AntNet 5. Backward ant pops its stack to know the next hop node A E F C G D 5A 7G 9D 0S S

1 2 AntNet 5. Backward ant pops its stack to know the next hop node A E F C G D 5A 7G 0S S

2 1 3 AntNet 5. Backward ant pops its stack to know the next hop node A E F C G D 5A 0S S

AntNet 5. Backward ant pops its stack to know the next hop node A S E F C G D 0S

AntNet 6. Whenever the Backward ant arrives a node, it updates 2 things: 1. A List Trip(  i,  i 2 ) 2. The Routing Table A E F C G D S

3 1 4 AntNet A E F C G D S Change A List Trip(  i,  i 2 ) It estimates arithmetic mean values  i and associated variances  i 2 for trip times from the node itself to all the nodes i in the network

AntNet 2. Change The Routing Table A E F C G D S Dest.Prob.NextHop D0.50A D F E A E F G F G A Dest.Prob.NextHop D0.75A D0.25F E0.50A E F G F G A OLD NEW

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

Other Routing Algorithms Performance Comparisons OSPF a robust routing protocol used in the internet BF asynchronous distributed Bellman Ford algorithm with dynamic link metrics SPF link state algorithm with a dynamic metric for link cost evaluations SPF_1FSPF with only 1 step of flooding DaemonIdeal algorithm

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

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

Traffic Patterns Experimental Settings Static Model Constant bit rate Dynamic Model Variable bit rate

Geographical Distribution of Traffic Experimental Settings Uniform-deterministic distribution Uniform-random distribution Uniform-deterministic-hot-spots Uniform-random-hot-spots

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

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)

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

AntNet shows a robust behavior Reaction time of algorithm is acceptable Impact on network resources is neglectable

Strengths and Possible Weaknesses StrengthsPossible 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 AntNet: new algorithm for adaptive routing Stigmergy 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

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 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 Microrobots

Community behavior: Clustering around food The Ants: A Community of Microrobots

Questions?