Authors:
Anabela Moreira Bernardino
1
;
Eugénia Moreira Bernardino
1
;
Juan Manuel Sánchez-Pérez
2
;
Juan Antonio Gomez Pulido
2
and
Miguel Ángel Vega-Rodríguez
2
Affiliations:
1
Polytechnic Institute of Leiria, Portugal
;
2
University of Extremadura, Spain
Keyword(s):
Weighted ring Arc-Loading problem, Particle swarm optimization, Local search, Optimization.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Bio-inspired Hardware and Networks
;
Computational Intelligence
;
Evolutionary Computing
;
Soft Computing
;
Swarm Intelligence
Abstract:
Massive growth of the Internet traffic in last decades has motivated the design of high-speed optical networks. Resilient Packet Ring (RPR), also known as IEEE 802.17, is a standard designed for the optimized transport of data traffic over optical fiber ring networks. Its design is to provide the resilience found in SONET/SDH networks but instead of setting up circuit oriented connections, providing a packet based transmission. This is to increase the efficiency of Ethernet and IP services. In this paper, a weighted ring arc-loading problem (WRALP) is considered which arises in engineering and planning of the RPR systems (combinatorial optimization NP- complete problem). Specifically, for a given set of non-split and uni-directional point-to-point demands (weights), the objective is to find the routing for each demand (i.e., assignment of the demand to either clockwise or counter-clockwise ring) so that the maximum arc load is minimized. This paper suggests four variants of Particle
Swarm Optimization (PSO), combined with a Local Search (LS) method to efficient non-split traffic loading on the RPR. Numerical simulation results show the effectiveness and efficiency of the proposed methods.
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