Comparing Artificial Bees Colony Algorithm and Firefly Algorithm to Achieve Optimization in Route Selection Processing Time in VANETs
Abstract
In achieving Intelligent Transportation System (ITS), a new trending area in networking is Vehicular Ad-hoc Networks (VANETs). It is a sub branch of Mobile Ad-hoc Networks (MANETs) where all the nodes or devices are interlinked and interconnected wirelessly. The challenges that a VANET faces while communicating within a network are signal fading, routing decision making and connectivity hitch. All these three mentioned problems have already been discussed and well researched in history by using conventional techniques as well as intelligent techniques based on artificial intelligence. Amongst all these three issues we are focusing on mitigating decision making problem for optimal route selection. In order to solve this issue, researchers have found that meta-heuristic intelligent algorithms such as, Artificial Bees Colony (ABC) and Firefly Algorithm (FFA) are more efficient algorithms as compared to traditional approach. In this paper we compared ABC and FFA to check which algorithm runs faster in order to achieve routing decision in lesser time
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