Vehicular Cloud Service Provider Selection: A Flexible Approach

Abstract

Vehicular Cloud (VC) is an emerging paradigm where vehicles having sufficient resources act as mobile cloud servers by offering a variety of services to user vehicles. To consume a cloud service on the move, a user vehicle must first identify the most stable vehicles, relatively to its motion, capable of providing the service, then select the most suitable service according to its preferences and service provider quality or constraints. In this paper, we introduce a link stability metric based on a generic relative motion model among vehicles to form a stable cloud and address vehicular cloud service selection by using linguistic quantifiers and fuzzy quantified propositions aggregating efficiently both user preferences and service constraints to rank service providers from the most to the least satisfactory. To break ties, we also define new parameters, called least satisfactory proportion (lsp) and greatest satisfactory proportion (gsp). Simulation results show that the link stability achieves generic motion and the selection approach allows a good successful service consumption rate while reducing latency.