Adaptive Uplink/Downlink Bandwidth Allocation for Dual Deadline Information Services in Vehicular Networks

With recent advances in information and communication technologies, vehicular networks become a promising paradigm in enabling various intelligent transportation systems (ITS). Efficient data update and dissemination are one of the fundamental requirements for realizing emerging ITS applications. In this paper, we first propose a two-layer architecture for dual deadline information services in vehicular networks, in which bandwidth resources are expected to be allocated adaptively for soft deadline data update and hard deadline data dissemination. Subsequently, we present an Age of Information (AoI) model to capture the quality of soft deadline temporal information, and formulate a Data Update and Dissemination (DUD) problem, which aims to minimize the average AoI and maximize the system service ratio. Further, we propose an Adaptive Request Bandwidth Scheduling (ARBS) algorithm, which makes scheduling decisions with respect to uplink and downlink bandwidth allocation and the selection of corresponding data items to be updated and disseminated. Finally, we give an extensive performance evaluation, which conclusively demonstrates that the proposed algorithm is able to effectively improve the bandwidth efficiency and enhance the service quality.