Preventive Assignment of Regenerator in Translucent Optical Networks

Fontinele, Alexandre; Santos, Iallen; Durães, Gilvan Martins; Maranhao, J.; Soares, André

doi:10.1109/sbrc.2014.42

Cited by 1 publication

(2 citation statements)

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“…The presented analytical model [17] was used to obtain the network BP, which was used as an evaluation function (objective function) in the process of searching for the MCSP solution. Then, all four routing solutions obtained with the DJK, BSR, BSR-DS and ACO-BSR strategies were simulated using the TONetS (Transparent Optical Network Simulator), a simuation tool developed to study RWA algorithms, survivability techniques and wavelength converter placement in all-optical networks [3,5,7,18]. The traffic load was uniformly distributed among all of the pairs (o, d), and the requests were generated following a Poisson process with mean λ and an exponentially distributed time retention with mean 1/µ.…”

Section: Performance Evaluationmentioning

confidence: 99%

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Ant Colony Optimization Applied to the Problem of Choosing the Best Combination among M Combinations of Shortest Paths in Transparent Optical Networks

Brasileiro

Santos

Soares

et al. 2016

Journal of Artificial Intelligence and Soft Computing Research

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This paper presents an attempt to solve the problem of choosing the best combination among the M combinations of shortest paths in optical translucent networks. Fixed routing algorithms demands a single route to each pair of nodes. The existence of multiple shortest paths to some pairs of nodes originates the problem of choose the shortest path which fits better the network requests. The algorithm proposed in this paper is an adaptation of Ant Colony Optimization (ACO) metaheuristic and attempt to define the set of routes that fits in an optimized way the network conditions, resulting in reduced number of blocked requests and better adjusted justice in route distribution. A performance evaluation is conducted in real topologies by simulations, and the proposed algorithm shows better performance between the compared algorithms.

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Section: Performance Evaluationmentioning

confidence: 99%

“…Both are real topologies located in US territory. Because the topologies occupy an extensive area and have an increasing number of users spread all around the US territory, both are frequently used in studies [2,4,5,18]. Table 4 shows the values used for ACO-BSR parameters.…”

Section: Performance Evaluationmentioning

confidence: 99%