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A Coral Reefs Optimization algorithm with substrate layer for robust Wi-Fi channel assignment

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Abstract

In this paper, we tackle a problem of frequency assignment in Wi-Fi networks with a novel evolutionary-type algorithm. In this version of the problem, we consider the interferences originated by the access points, and also by the clients and all the 11 available channels in the 2.4 GHz Wi-Fi frequency band. The proposed evolutionary-type algorithm is the Coral Reefs Optimization approach with substrate layer (CRO-SL). It is a recently proposed algorithm, which simulates the processes which occur in real coral reefs, including the reproduction and fight for the space of living corals. This version of the algorithm includes a layer of “substrates” which allows using different search patterns jointly in the algorithm. This way, the CRO-SL is able to apply search patterns such as harmony search, differential evolution, Gaussian-based mutations and other traditional and novel search procedures, including local search algorithms, within a single population of solutions. We show the good performance of the proposed approach in a real case study of Wi-Fi frequency assignment, in the Polytechnic School building of the Universidad de Alcalá (Spain), where different realistic scenarios of the problem have been simulated and successfully solved with the CRO-SL algorithm.

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References

  • Abusubaih M (2016) Using partially overlapping channels in home 802.11g WLANs. Wirel Pers Commun 88(2):295–303

    Article  Google Scholar 

  • Achanta M (2006) Method and apparatus for least congested channel scan for wireless access points. US Patent number: US20060072602 A1

  • Bazzi A (2011) On uncoordinated multi-user multi-RAT combining. In: Proceedings of the IEEE vehicular technology conference, VTC Fall, pp 1–6

  • Bermejo E, Chica M, Damas S, Salcedo-Sanz S, Cordón O (2018) Coral Reef Optimization with substrate layers for medical image registration. Swarm Evolut Comput 42:138–159

    Article  Google Scholar 

  • Beyer HG, Schwefel HP (2002) Evolution strategies—a comprehensive introduction. Nat Comput 1(1):3–52

    Article  MathSciNet  MATH  Google Scholar 

  • Bäck T, Schwefel HP (1993) An overview of evolutionary algorithms for parameter optimization. Evolut Comput 1:1–23

    Article  Google Scholar 

  • Chen JK, De Veciana G, Rappaport TS (2007) “Improved measurement-based frequency allocation algorithms for wireless networks. In: Proceedings of the IEEE global telecommunications conference, GLOBECOM’07, pp 4790–4795

  • Chieochan S, Hossain E, Diamond J (2010) Channel assignment schemes for infrastructure-based 802.11 WLANs: a survey. IEEE Commun Surv Tutor 12(1):124–136

    Article  Google Scholar 

  • Cortés P, García JM, Onieva L (2008) Viral systems: a new bio-inspired optimisation approach. Comput Oper Res 35(9):2840–2860

    Article  MATH  Google Scholar 

  • de la Hoz E, Gimenez-Guzman JM, Marsa-Maestre I, Orden D (2015) Automated negotiation for resource assignment in wireless surveillance sensor networks. Sensors 15(11):29547–29568

    Article  Google Scholar 

  • De La Hoz E, Marsa-Maestre I, Gimenez-Guzman JM, Orden D, Klein M (2017) Multi-agent nonlinear negotiation for Wi-Fi channel assignment. In: Proceedings of the 16th conference on Autonomous Agents and MultiAgent Systems, International Foundation for Autonomous Agents and Multiagent Systems, pp 1035–1043

  • Del Ser J, Matinmikko M, Gil-López S, Mustonen M (2012) Centralized and distributed spectrum channel assignment in cognitive wireless networks: a Harmony search approach. Appl Soft Comput 12:921–930

    Article  Google Scholar 

  • Dorigo M, Maziezzo V, Colorni A (1996) The ant system: optimization by a colony of cooperating ants. IEEE Trans Syst Man Cybern B 26(1):29–41

    Article  Google Scholar 

  • Eiben AE, Smith JE (2003) Introduction to evolutionary computing. Springer-Verlag, Natural Computing Series 1st edition

  • Elwekeil M, Alghoniemy M, El-Khamy M, Furukawa H, Muta O (2012). Optimal channel assignment for IEEE 802.11 multi-cell WLANs. In: Proceedings of the 20th IEEE European signal processing conference (EUSIPCO), pp 694–698

  • Ficco M, Esposito C, Palmieri F, Castiglione A (2018) A coral-reefs and Game Theory-based approach for optimizing elastic cloud resource allocation. Future Gener Comput Syst 78:343–352

    Article  Google Scholar 

  • Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: Harmony search. Simulation 76(2):60–68

    Article  Google Scholar 

  • Geier J How to define minimum SNR values for signal coverage. http://www.wireless-nets.com/resources/tutorials/define_SNR_values.html

  • Grassberger P, Procaccia I (1983) Characterization of strange attractors. Phys Rev Lett 50(5):346–349

    Article  MathSciNet  MATH  Google Scholar 

  • Green DB, Obaidat AS (2002) An accurate line of sight propagation performance model for ad-hoc 802.11 wireless LAN (WLAN) devices. In: Proceedings of the IEEE international conference on communications, ICC 2002, vol 5, pp 3424–3428

  • Haidar M, Akl R, Al-Rizzo H, Chan Y (2007) Channel assignment and load distribution in a power-managed WLAN. In: Proceedings of the 15th IEEE international symposium on personal, indoor and mobile radio communications, PIMRC’07, pp 1–5

  • Jensen TR, Toft B (2011) Graph coloring problems, vol 39. Wiley, Hoboken

    MATH  Google Scholar 

  • Karaboga D, Basturk B (2008) On the performance of the artificial bee colony (ABC) algorithm. Appl Soft Comput 8:687–697

    Article  Google Scholar 

  • Kaveh A, Dadras A (2017) A novel meta-heuristic optimization algorithm: thermal exchange optimization. Adv Eng Softw 110:69–84

    Article  Google Scholar 

  • Kaveh A, Khayatazad M (2012) A new meta-heuristic method: ray optimization. Comput Struct 112–113:283–294

    Article  Google Scholar 

  • Kaveh A, Mahdavi VR (2014) Colliding bodies optimization: a novel meta-heuristic method. Comput Struct 139:18–27

    Article  Google Scholar 

  • Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of the 4th IEEE international conference on neural networks, pp 1942–1948

  • Kephart JO (1994) A biologically inspired immune system for computers. In: Proceedings of the artificial life IV: the fourth international workshop on the synthesis and simulation of living systems, MIT Press, pp 130–139

  • Kirpatrick D, Gerlatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671–680

    Article  MathSciNet  Google Scholar 

  • Klein M, Faratin P, Sayama H, Bar-Yam Y (2003) Negotiating complex contracts. Group Decis Negotiat 12(2):111–125

    Article  MATH  Google Scholar 

  • Lang F, Fink A (2015) Learning from the metaheuristics: protocols for automated negotiations. Group Decis Negotiat 24:299–332

    Article  Google Scholar 

  • Lee Y, Kim K, Choi Y (2002) Optimization of AP placement and channel assignment in wireless LANs. In: Proceedings of the 27th annual IEEE conference on local computer networks, pp 831–836

  • Li M, Miao C, Leung C (2015) A Coral Reef Algorithm based on learning automata for the coverage control problem of heterogeneous directional sensor networks. Sensors 15:3061730635

    Google Scholar 

  • Mahonen P, Riihijarvi J, Petrova M (2004) Automatic channel allocation for small wireless local area networks using graph colouring algorithm approach. In: Proceedings of the 15th IEEE international symposium on personal, indoor and mobile radio communications, PIMRC’04, vol 1, pp 536–539

  • Marsa-Maestre I, López-Carmona MA, Velasco JR, de la Hoz E (2010) Avoiding the prisoner’s dilemma in auction-based negotiations for highly rugged utility spaces. In: Proceedings of the 9th international conference on autonomous agents and multiagent systems, vol 1, pp 425–432

  • Medeiros IG, Xavier-Júnior JC, Canuto AM (2015) Applying the Coral Reefs Optimization algorithm to clustering problems. In: Proceedings of the international joint conference on neural networks (IJCNN), pp 1–8

  • Mehrabian AR, Lucas C (2006) A novel numerical optimization algorithm inspired from weed colonization. Ecol Inform 1:355–366

    Article  Google Scholar 

  • Michaloliakos A, Rogalin R, Zhang Y, Psounis K, Caire G (2016) Performance modeling of next-generation WiFi networks. Comput Netw 105:150–165

    Article  Google Scholar 

  • Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61

    Article  Google Scholar 

  • Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67

    Article  Google Scholar 

  • Mishra A, Brik V, Banerjee S, Srinivasan A, Arbaugh WA (2006) A client-driven approach for channel management in wireless LANs. In: Proceedings of the INFOCOM conference

  • Müller S, Airaghi S, Marchetto J (2002) Optimization based on bacterial chemotaxis. IEEE Trans Evolut Comput 6(1):16–29

    Article  Google Scholar 

  • Ng SWK, Szymanski TH (2012) Interference measurements in an 802.11n wireless mesh network testbed. In: Proceedings of the 25th IEEE Canadian conference on electrical computer engineering (CCECE), pp 1–6

  • Oftadeh R, Mahjoob MJ, Shariatpanahi M (2010) A novel meta-heuristic optimization algorithm inspired by group hunting of animals: hunting search. Comput Math Appl 60(7):2087–2098

    Article  MATH  Google Scholar 

  • Orden D, Gimenez-Guzman JM, Marsa-Maestre I, de la Hoz E (2018) Spectrum graph coloring and applications to Wi-Fi channel assignment. Symmetry 10(3):65

    Article  MATH  Google Scholar 

  • Passino KM (2002) Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst Mag 22:52–67

    Article  Google Scholar 

  • Rashedi E, Nezamabadi-pour H, Saryazdi S (2009) GSA: a gravitational search algorithm. Inf Sci 179:2232–2248

    Article  MATH  Google Scholar 

  • Riggio R, Rasheed T, Testi S, Granelli F, Chlamtac I (2011) Interference and traffic aware channel assignment in WiFi-based wireless mesh networks. Ad Hoc Netw 9:864–875

    Article  Google Scholar 

  • Salcedo-Sanz S (2016) Modern meta-heuristics based on nonlinear physics processes: a review of models and design procedures. Phys Rep 655:1–70

    Article  MathSciNet  Google Scholar 

  • Salcedo-Sanz S (2017) A review on the coral reefs optimization algorithm: new development lines and current applications. Prog Artif Intell 6:1–15

    Article  Google Scholar 

  • Salcedo-Sanz S, Del Ser J, Landa-Torres I, Gil-López S, Portilla-Figueras JA (2014a) The Coral Reefs Optimization algorithm: a novel metaheuristic for efficiently solving optimization problems. The Scientific World Journal, vol 2014, Article ID: 739768

  • Salcedo-Sanz S, Gallo-Marazuela D, Pastor-Sánchez A, Carro-Calvo L, Portilla-Figueras A, Prieto L (2014b) Offshore wind farm design with the Coral Reefs Optimization algorithm. Renew Energy 63:109–115

    Article  Google Scholar 

  • Salcedo-Sanz S, Pastor-Sánchez A, Prieto L, Blanco-Aguilera A, García-Herrera R (2014c) Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization Extreme learning machine approach. Energy Convers Manag 87:10–18

    Article  Google Scholar 

  • Salcedo-Sanz S, Casanova-Mateo C, Pastor-Sánchez A, Sánchez-Girón M (2014d) Daily Global solar radiation prediction based on a hybrid coral reefs optimization—extreme learning machine approach. Solar Energy 105:91–98

    Article  Google Scholar 

  • Salcedo-Sanz S, Sánchez-García JE, Portilla-Figueras JA, Jiménez-Fernández S, Ahmadzadeh AM (2014e) A Coral-Reefs Optimization algorithm for the optimal service distribution problem in mobile radio access networks. Trans Emerg Telecommun Technol 25(11):1057–1069

    Article  Google Scholar 

  • Salcedo-Sanz S, García-Díaz P, Portilla-Figueras JA, Del Ser J, Gil-López S (2014f) A Coral Reefs Optimization algorithm for optimal mobile network deployment with electromagnetic pollution control criterion. Appl Soft Comput 24:239–248

    Article  Google Scholar 

  • Salcedo-Sanz S, García-Díaz P, Del Ser J, Bilbao MN, Portilla-Figueras JA (2016a) A novel Grouping Coral Reefs Optimization algorithm for optimal mobile network deployment problems under electromagnetic pollution and capacity control criteria. Expert Syst Appl 55:388–2402

    Article  Google Scholar 

  • Salcedo-Sanz S, Camacho-Gómez C, Molina D, Herrera F (2016b) A Coral Reefs Optimization algorithm with substrate layers and local search for large scale global optimization. IEEE Congress on Evolutionary Computation, Vancouver

    Book  Google Scholar 

  • Salcedo-Sanz S, Camacho-Gómez C, Mallol-Poyato R, Jiménez-Fernández S, Del Ser J (2016c) A novel Coral Reefs Optimization algorithm with substrate layers for optimal battery scheduling optimization in micro-grids. Soft Comput 20(11):4287–4300

    Article  Google Scholar 

  • Salcedo-Sanz S, Muñoz-Bulnes J, Vermeij M (2017a) New Coral Reefs-based approaches for the model type selection problem: a novel method to predict a nation’s future energy demand. Int J Bio-inspired Comput 10(3):145–158

    Article  Google Scholar 

  • Salcedo-Sanz S, Camacho-Gómez C, Magdaleno A, Pereira E, Lorenzana A (2017b) Structures vibration control via tuned mass dampers using a co-evolution coral reefs optimization algorithm. J Sound Vib 393:62–75

    Article  Google Scholar 

  • Salcedo-Sanz S, Deo RC, Cornejo-Bueno L, Camacho-Gómez, Ghimire S (2018a) An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia. Appl Energy 209:79–94

  • Salcedo-Sanz S, García-Herrera R, Camacho-Gómez C, Aybar-Ruíz A, Alexandre E (2018b) Wind power field reconstruction from a reduced set of representative measuring points. Appl Energy 228:1111–1121

    Article  Google Scholar 

  • Seyedebrahimi M, Bouhafs F, Raschella A, Mackay M, Shi Q (2016) SDN-based channel assignment algorithm for interference management in dense Wi-Fi networks. In: Proceedings of the IEEE European conference on networks and communications (Eu-CNC), pp 128–132

  • Silva HM, Canuto AM, Medeiros Inácio G, Xavier-Júnior JC (2016) Cluster ensembles optimization using the Coral reefs Optimization Algorithm. Artificial Neural Networks and Machine Learning—ICANN 2016, Lecture Notes in Computer Science, vol 9887, pp 275–282

  • Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702–713

    Article  Google Scholar 

  • Storn R, Price K (1997) Differential Evolution—a simple and efficient heuristic for global optimization over continuous spaces. J Global Optim 11:341–359

    Article  MathSciNet  MATH  Google Scholar 

  • Soua R, Minet P (2015) Multichannel assignment protocols in wireless sensor networks: a comprehensive survey. Pervasive Mobile Comput A 16:2–21

    Article  Google Scholar 

  • Thakur R, Kotagi VJ, Ram Murthy CS (2017) Resource allocation and cell selection framework for LTE-unlicensed femtocell networks. Comput Netw 129:273–283

    Article  Google Scholar 

  • Vermeij MJ (2005) Substrate composition and adult distribution determine recruitment patterns in a Caribbean brooding coral. Mar Ecol Prog Ser 295:123–133

    Article  Google Scholar 

  • Yang XS, Deb S (2009) Cuckoo search via Lévy flights. In: Proceedings of the World conference on nature & biologically inspired computing, pp 210–214

  • Yang XS (2010) A new metaheuristic Bat-inspired algorithm. In: Proceedings of the nature inspired cooperative strategies for optimization, studies in computational intelligence, vol 284, Springer, pp 6574

  • Yang Z, Zhang T, Zhang D (2016) A novel algorithm with differential evolution and coral reef optimization for extreme learning machine training. Cognit Neurodyn 10(1):73–83

    Article  MathSciNet  Google Scholar 

  • Yao X, Liu Y, Lin G (1999) Evolutionary programming made faster. IEEE Trans Evol Comput 3(2):82–102

    Article  Google Scholar 

  • Wang H, Lu X, Zhang X, Wang Q, Deng Y (2014) A bio-inspired method for the constrained shortest path problem. The Scientific World Journal, vol 2014, art. ID: 271280

  • Wang J, Shi W, Cui K, Jin F, Li Y (2015) Partially overlapped channel assignment for multi-channel multi-radio wireless mesh networks. EURASIP J Wirel Commun Netw 2015:1–25

    Google Scholar 

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Acknowledgements

This work has been partially supported by the project TIN2014-54583-C2-2-R of the Spanish Ministerial Commission of Science and Technology (MICYT), by the Spanish Ministry of Economy and Competitiveness grants TIN2016-80622-P (AEI/FEDER, UE) and TIN2014-61627-EXP and by the Comunidad Autónoma de Madrid, under project number S2013ICE-2933_02.

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Authors and Affiliations

  1. Department of Signal Processing and Communications, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain

    Carlos Camacho-Gómez & Sancho Salcedo-Sanz

  2. Computer Engineering Department, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain

    Ivan Marsa-Maestre & Jose Manuel Gimenez-Guzman

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  1. Carlos Camacho-Gómez
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  2. Ivan Marsa-Maestre
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  3. Jose Manuel Gimenez-Guzman
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  4. Sancho Salcedo-Sanz
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Correspondence to Jose Manuel Gimenez-Guzman.

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Camacho-Gómez, C., Marsa-Maestre, I., Gimenez-Guzman, J.M. et al. A Coral Reefs Optimization algorithm with substrate layer for robust Wi-Fi channel assignment. Soft Comput 23, 12621–12640 (2019). https://doi.org/10.1007/s00500-019-03815-9

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