Improving hybrid ad hoc networks: The election of gateways |
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| Affiliation: | 1. Department of Electrical and Electronics Engineering, Government College of Engineering, Tirunelveli, India;2. Department of Electrical and Electronics Engineering, Anna University, Chennai, India;1. Department of Computer Science and Information Engineering, Tamkang University, Taipei 251, Taiwan;2. Department of Computer Science and Information Engineering, National Cheng Kung University, 701, Taiwan;3. Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung 811, Taiwan;4. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 804, Taiwan;1. École internationale des sciences du traitement de l’information (EISTI), avenue du parc, 95000 Cergy-Pontoise, France;2. Université de Paris-Est Créteil (UPEC), LISSI (EA 3956), 122, rue Paul Armangot, 94400 Vitry sur Seine, France;1. Department of Statistics, Faculty of Arts and Sciences, Yildiz Technical University, Turkey;2. Department of Electronics and Communications Engineering, Faculty of Electrical and Electronics Engineering, Yildiz Technical University, Turkey;3. Department of Biomedical Engineering, Faculty of Electrical and Electronics Engineering, Yildiz Technical University, Turkey;4. Computational Science and Engineering, Istanbul Technical University, Turkey;5. Molecular Biology-Biotechnology, Istanbul Technical University and Iontek A.?., Istanbul, Turkey |
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| Abstract: | The selection of an appropriate and stable route that enables suitable load balancing of Internet gateways is an important issue in hybrid mobile ad hoc networks. The variables employed to perform routing must ensure that no harm is caused that might degrade other network performance metrics such as delay and packet loss. Moreover, the effect of such routing must remain affordable, such as low losses or extra signaling messages. This paper proposes a new method, Steady Load Balancing Gateway Election, based on a fuzzy logic system to achieve this objective. The fuzzy system infers a new routing metric named cost that considers several networks performance variables to select the best gateway. To solve the problem of defining the fuzzy sets, they are optimized by a genetic algorithm whose fitness function also employs fuzzy logic and is designed with four network performance metrics. The promising results confirm that ad hoc networks are characterized by great uncertainty, so that the use of Computational Intelligence methods such as fuzzy logic or genetic algorithms is highly recommended. |
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| Keywords: | Ad hoc routing Ad hoc load balancing Hybrid MANET Fuzzy logic routing Genetic-algorithms Multi-objective optimization |
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