Title
Solving ring loading problems using bio-inspired algorithms
Abstract
In the last years, several combinatorial optimisation problems have arisen in the communication networks field. In many cases, to solve these problems it is necessary the use of emergent optimisation algorithms. The Weighted Ring Loading Problem (WRLP) is an important optimisation problem in the communication optical network field. When managed properly, the ring networks are uniquely suited to deliver a large amount of bandwidth in a reliable and inexpensive way. An optimal load balancing is very important, as it increases the system's capacity and improves the overall ring performance. The WRLP consists on the design, in a communication network of a transmission route (direct path) for each request, such that high load on the arcs/edges is avoided, where an arc is an edge endowed with a direction. In this paper we study this problem in two different ring types: Synchronous Optical NETworking (SONET) rings and Resilient Packet Ring (RPR). In RPR the purpose is to minimise the maximum load on the ring Arcs (WRALP). In SONET rings the purpose is to minimise the maximum load on the ring Edges (WRELP). The load of an arc is defined as the total weight of those requests that are routed through the arc in its direction and the load of an edge is the total weight of the routes traversing the edge in either direction. In this paper we study both problems without demand splitting and we propose three bio-inspired algorithms: Genetic Algorithm with multiple operators, Hybrid Differential Evolution with a multiple strategy and Hybrid Discrete Particle Swarm Optimisation. We also perform comparisons with other algorithms from literature. Simulation results verify the effectiveness of the proposed algorithms.
Year
DOI
Venue
2011
10.1016/j.jnca.2010.11.003
J. Network and Computer Applications
Keywords
DocType
Volume
combinatorial optimisation problem,different ring type,overall ring performance,bio-inspired algorithm,optimal load balancing,Communication networks,Weighted Ring Edge-Loading Problem,Swarm Intelligence,ring network,Weighted Ring Arc-Loading Problem,high load,ring loading problem,Optimisation algorithms,Bio-inspired algorithms,ring Edges,total weight,maximum load,ring Arcs
Journal
34
Issue
ISSN
Citations 
2
Journal of Network and Computer Applications
6
PageRank 
References 
Authors
0.45
27
5