Fast simulation of rare events in queueing and reliability models
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Ant-based load balancing in telecommunications networks
Adaptive Behavior
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Future Generation Computer Systems
ACM Transactions on Computer Systems (TOCS)
Stability issues in OSPF routing
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Experience in black-box OSPF measurement
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Routing, Flow, and Capacity Design in Communication and Computer Networks
Routing, Flow, and Capacity Design in Communication and Computer Networks
A Shortest-Path Network Problem Using an Annealed Ant System Algorithm
Proceedings of the Fourth Annual ACIS International Conference on Computer and Information Science
A comprehensive review of nature inspired routing algorithms for fixed telecommunication networks
Journal of Systems Architecture: the EUROMICRO Journal - Special issue: Nature-inspired applications and systems
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
ICUCT'06 Proceedings of the 1st international conference on Ubiquitous convergence technology
Restoration performance vs. overhead in a swarm intelligence path management system
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Self-tuned refresh rate in a swarm intelligence path management system
IWSOS'06/EuroNGI'06 Proceedings of the First international conference, and Proceedings of the Third international conference on New Trends in Network Architectures and Services conference on Self-Organising Systems
Design and analysis of a bio-inspired search algorithm for peer to peer networks
Self-star Properties in Complex Information Systems
A short convergence proof for a class of ant colony optimizationalgorithms
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Convergence properties of the cross-entropy method for discrete optimization
Operations Research Letters
Revisiting the Auto-Regressive Functions of the Cross-Entropy Ant System
IWSOS '09 Proceedings of the 4th IFIP TC 6 International Workshop on Self-Organizing Systems
Ant system for service deployment in private and public clouds
Proceedings of the 2nd workshop on Bio-inspired algorithms for distributed systems
warm intelligence heuristics for component deployment
EUNICE'10 Proceedings of the 16th EUNICE/IFIP WG 6.6 conference on Networked services and applications: engineering, control and management
Opportunistic ant-based path management for wireless mesh networks
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Ant-based multipath routing for wireless mesh networks
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
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CEAS (cross entropy ant system) is a distributed, robust and adaptive swarm intelligence system for path management in communication networks. This paper focuses on strategies for handling the overhead in terms of processing cycles, memory storage, and number of management packets (ants) generated by CEAS when the state of the network changes. Pheromone sharing is introduced such that virtual connections with common sub-paths are sharing information and cooperate in the path finding when the paths have the same destination and the same objective function. The sharing of information reduces the required memory in each node significantly on the expense of an increase in the size of the management packets. However, the packets are still rather small. The cooperation also leads to an improvement in convergence rates which again results in reduced transmission overhead. A rate adjustment scheme is also proposed. The scheme is self-tuned and detects state changes implicitly and sets packet rates accordingly by monitoring parameter values in the management system. Rate adaptation can be done both in the network nodes and at the end-points of a virtual path. Compared to a fixed rate strategy the self-tuned strategies show a significant reduction in the number of packets generated, while maintaining the same data packet delay and service availability level. The self-tuned rate adjustment in the network nodes provides fast restoration with short path detection times, which ensures high service availability. The self-tuned ant rate in the end-points avoids flooding the network with management packets when these are not required. The performance and overhead of CEAS are compared to those of the link state routing currently in use in today's networks. The results show that CEAS outperforms link state routing both with respect to performance and overhead when the network experiences transient link failures, while the opposite is the case with long lived failures.