Intelligent Technique Based on Enhanced Metaheuristic for Optimization Problem in Internet of Things and Wireless Sensor Network

Forthelastdecade,therehasbeenanintensiveresearchdevelopmentintheareaofwirelesssensor networks(WSN).ThisismainlyduetotheirgrowinginterestinseveralapplicationsoftheInternet ofThings(IoT).Severalissuesarethusdiscussedsuchasnodelocalization,acapabilitythatishighly desirableforperformanceevaluationinmonitoringapplications.Thelocalizationaimistolookfor precisegeographicalpositionsofsensors.Recently,swarmintelligencetechniquesaresuggestedto dealwithlocalizationchallengeandlocalizationisseenasanoptimizationproblem.Inthisarticle,an EnhancedFruitFlyOptimizationAlgorithm(EFFOA)isproposedtosolvethelocalization.EFFOAhas astrongcapacitytocalculatethepositionoftheunknownnodesandconvergesiterativelytothebest solution.Distributingandexploitingnodesisachiefchallengetotestingthescalabilityperformance. theEFFOAissimulatedundervariantstudiesandscenarios.inaddition,acomparativeexperimental studyprovesthatEFFOAoutperformssomeofthewell-knownoptimizationalgorithms. KEyWORdS Intelligent Technique, Internet Of Things, Localization Time, Metaheuristic, Node Localization, Optimization Problem, Scalability, Wireless Sensor Network

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