Title
A Parallel Multiobjective Artificial Bee Colony Algorithm for Dealing with the Traffic Grooming Problem
Abstract
This work presents a novel parallel multiobjective approach based on the Artificial Bee Colony algorithm for grooming low-speed traffic requests onto high-capacity optical channels. The traffic grooming problem in mesh optical networks is an NP-hard problem, so the usage of metaheuristics and parallelism jointly for increasing the network performance is a great option in order to reduce execution times. The parallel multiobjective approach is implemented by using OpenMP. We have measured the speedup and efficiency obtained by our parallel approach with 2, 4, 8, and 16 cores. Efficient numerical results are reported in the experimental phase conducted on two optical networks. Finally, we present a comparative study with traditional methods; in which we show that the usage of swarm intelligence outperforms previous results published in the literature.
Year
DOI
Venue
2012
10.1109/HPCC.2012.17
HPCC-ICESS
Keywords
Field
DocType
parallel multiobjective approach,high-capacity optical channel,comparative study,artificial bee colony algorithm,low-speed traffic request,optical network,mesh optical network,novel parallel multiobjective approach,traffic grooming problem,colony algorithm,parallel approach,np-hard problem,parallel multiobjective artificial bee,metaheuristics,swarm intelligence,evolutionary computation,topology,optical mesh networks,traffic grooming,multi core,parallel processing,multiobjective optimization,network topology,public domain software,np hard problem,mathematical model,tin
Artificial bee colony algorithm,Computer science,Swarm intelligence,Parallel computing,Evolutionary computation,Multi-objective optimization,Multi-core processor,Metaheuristic,Speedup,Traffic grooming,Distributed computing
Conference
ISSN
Citations 
PageRank 
2576-3504
4
0.39
References 
Authors
8
4