Adaptive Virtual RSU Scheduling for Scalable Coverage under Bidirectional Vehicle Traffic Flow

Abstract

Over the past decades, vehicular ad hoc networks (VANETs) have been a core networking technology to provide drivers and passengers with safety and convenience. As a new emerging technology, the vehicular cloud computing (VCC) can provide cloud services for various data-intensive applications in VANETs, such as multimedia streaming. However, the vehicle mobility and intermittent connectivity present challenges to the large-scale data dissemination with underlying computing and networking architecture. In this paper, we will explore the service scheduling of virtual RSUs for diverse request demands in the dynamic traffic flow in vehicular cloud environment. Specifically, we formulate the RSU allocation problem as maximum service capacity with multiple-source and multiple-destination, and propose a bidirectional RSU allocation strategy. In addition, we formulate the content replication in distributed RSUs as the minimum replication set coverage problem in a two-layer mapping model, and analyze the solutions in different scenarios. Numerical results further prove the superiority of our proposed solution, as well as the scalability to various traffic condition variations.