Improved reinforcement computing to implement antnet-based routing using general NPS for ubiquitous environments

Authors:
Hyuntae Park;Byung In Moon;Sungho Kang
Affiliations:
Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea;School of Electrical Engineering & Computer Science, Kyungpook National University, Daegu, Korea;Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea
Venue:
ICUCT'06 Proceedings of the 1st international conference on Ubiquitous convergence technology
Year:
2006

Citing 2
Cited 1

AntNet: distributed stigmergetic control for communications networks

Journal of Artificial Intelligence Research
Ant colony optimization for routing and load-balancing: survey and new directions

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Overhead reduction in a distributed path management system

Computer Networks: The International Journal of Computer and Telecommunications Networking

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Abstract

In the ubiquitous convergence era, the traffic managements and quality of services will be made much of a role. Because traditional routing mechanisms are lacking scalability and adaptability, a kind of adaptive routing algorithm called AntNet has attracted the attention. AntNet is an adaptive agent-based routing algorithm that imitates the activities of the social insect. In AntNet, there are implementation constraints due to complex arithmetic calculations for determining a reinforcement value. Besides, a housekeeping core in network processors will be overwhelmed by increasing routing workload for a processing of agents. In this paper, we propose a new reinforcement computing algorithm to overcome these problems. This can be implemented efficiently on packet forwarding engines of conventional network processors. The simulation results show that the proposed AntNet is more adaptive and effective in the performance of the implementation than the original AntNet.