Load Balancing in Heterogeneous Networks using Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{fenton:cec2015,

• author = "Michael Fenton and David Lynch and Stepan Kucera and Holger Claussen and Michael O'Neill",
• title = "Load Balancing in Heterogeneous Networks using Grammatical Evolution",
• booktitle = "Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015)",
• editor = "Yadahiko Murata",
• pages = "70--76",
• year = "2015",
• address = "Sendai, Japan",
• month = "25-28 " # may,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming, grammatical evolution",
• DOI = "doi:10.1109/CEC.2015.7256876",
• abstract = "Grammatical Evolution (GE) is applied to the problem of load balancing in heterogeneous cellular network deployments (HetNets). HetNets are multi-tiered cellular networks for which load balancing is a scalable means to maximise network capacity, assuming similar traffic from all users. This paper describes a proof of concept study in which GE is used in a genetic algorithm-like way to evolve constants which represent cell power and selection bias in order to achieve load balancing in HetNets. A fitness metric is derived to achieve load balancing both locally in sectors and globally across tiers. Initial results show promise for GE as a heuristic for load balancing. This finding motivates a more sophisticated grammar to bring enhanced Inter-Cell Interference Coordination optimisation into an evolutionary framework.",
• notes = "1545 hrs 15434 CEC2015",

}

Genetic Programming entries for Michael Fenton David Lynch Stepan Kucera Holger Claussen Michael O'Neill

Citations