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

Presentation Content Introduction Routing Basics MAS- ACO AntNet Algorithm Conclusion Reference list

Introduction Rapid growth of networks Increase of network communication introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

What Is Routing? Routing is the act of moving information across a network from a source to a destination. introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Tasks of Routing The tasks of a routing protocol are determine the optimal paths route information introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Design Goals Optimality Simplicity and low overhead Rapid convergence Robustness and stability Flexibility introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Agent & multi-agent system Agent is a software that have some specification: Autonomy Reactivity Pro-activeness Social ability introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Mobile Agent A mobile agent is a software agent that can move between locations (mobility). introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Nature inspired algorithms PSO ABC GA ACO introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

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 introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

ACO (cont.) Based on ants method of finding food. Using to solve traveling salesman routing in networks load balancing introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Swarm intelligence introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Stigmergy A mechanism of indirect coordination between agents . introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

The process that ants search the shortest path introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Ants & routing 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. introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

AntNet 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. introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

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 introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

AntNet:Description (cont.) Two data structures stored in each network node: Routing table (P) An array mean the best trip time from i to j. variance introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

AntNet:Description (cont.) Outgoing Links Routing table Local traffic statistics Network Node(i) P11 P12 P1N P2N PmN, P21 Pm1 Pm2 ....... Network Nodes introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

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. introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

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. introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

AntNet algorithm (cont.) Pfd = Pfd + r(1- Pfd ) Pnd = Pnd - r Pnd , n  Nk, n  f introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

AntNet: Overview 1 3 4 2 5 6 Forward Ant (13) Backward Ant (13) At Node 2, Update Routing Information for 3 At Node 1, Update Routing Information for 3 and Update routing information for 2 introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Conclusion The main characteristics of AntNet algorithm Nature inspired, Adaptivity Inherent parallelism Sclalablity the Ant Colony Optimization can be applied to many other hard problems. introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

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 introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End

Questions, Comments? Thank You  introduction Routing basics MAS-ACO AntNet Algorithm Conclusion References End