MALTREAT - A Metaheuristic Algorithm for Allocation of Resources in Vehicular AD-HOC Networks

Abstract

Over time, Decision Support Technologies (DST) based on Intelligent Transport Systems (ITS) have undergone modernization through the remodeling of well-known techniques. In vehicular networks, clustering is employed to increase service capacity, where each vehicle can act as a repository of storage, processing, and memory resources while idle. However, due to limited resources and a highly dynamic topology, efficient algorithms are necessary to support decision-making during the allocation of these resources. This study proposes a meta-heuristic algorithm for resource allocation in vehicular ad-hoc networks called MALTREAT, which utilizes Harris Hawk Optimization (HHO) to optimize the search process for idle resources. Our results indicate that MALTREAT outperforms literature works in terms of resource allocation effectiveness, including higher volumes of allocated resources and served services, as well as a lower rate of denied services across all scenarios.