Meta-Heuristic Mechanism Based On Whale Optimization Algorithm For Tasks Allocation In Edge Computing

The number of vehicles in the world is growing, at the same time, it is also increasing the technology used in vehicles. Such vehicles share a large amount of information using different technologies. To make data available closer to vehicles and thus streamline communication, edge services are becoming a support for intelligent transport systems. However, this service has limited computational resources. Thus, optimizing the use of these resources is a challenge. In this way, this work propose a meta-heuristic mechanism based on the whale optimization algorithm to perform the decision-making process for resource allocation in an edge computing environment, named MARTIAL. Results show that our approach performed better when compared to other traditional algorithms. The mechanism proved to be efficient in maximizing the number of tasks served and minimizing blocks and denials.