Survivable Networks: Algorithms for Diverse Routing
Survivable Networks: Algorithms for Diverse Routing
Dynamic Routing of Bandwidth Guaranteed Multicasts with Failure Backup
ICNP '02 Proceedings of the 10th IEEE International Conference on Network Protocols
An Ultra-fast Shared Path Protection Scheme - Distributed Partial Information Management, Part II
ICNP '02 Proceedings of the 10th IEEE International Conference on Network Protocols
Diverse Routing for Shared Risk Resource Groups (SRRG) Failures in WDM Optical Networks
BROADNETS '04 Proceedings of the First International Conference on Broadband Networks
CoSE: A SRLG-Disjoint Routing Algorithm
ECUMN '07 Proceedings of the Fourth European Conference on Universal Multiservice Networks
First steps to the runtime complexity analysis of ant colony optimization
Computers and Operations Research
Graph transformation approaches for diverse routing in shared risk resource group (SRRG) failures
Computer Networks: The International Journal of Computer and Telecommunications Networking
Implementing an ACO Routing Algorithm for AD-HOC Networks
ICACTE '08 Proceedings of the 2008 International Conference on Advanced Computer Theory and Engineering
A pheromone-rate-based analysis on the convergence time of ACO algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
Resilience in multilayer networks
IEEE Communications Magazine
Free Search with Adaptive Differential Evolution Exploitation and Quantum-Inspired Exploration
Journal of Network and Computer Applications
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Failure resilience is a desired feature in communication networks, and different methods can be considered in order to achieve this feature. One of these methods is diverse Routing. In this paper, we are going to suggest a sort of diverse routing algorithm, which can find two maximal shared risk link group (SRLG) disjoint paths between a source and a destination node. This algorithm is based on ant colony optimization algorithm, which consists of three parts. These parts are graph transformation technique, finding two maximal edge-disjoint routes and reverse transformation. The final routes are always maximal SRLG disjoint. Simulation results show the efficiency of the proposed method.