Vehicle-cluster-based opportunistic relays for data collection in intelligent transportation systems

Abstract

Intelligent transportation system (ITS) is envisioned to greatly improve traffic and enhance safety on roads. ITS relies on a huge amount of data generated from roadside sensor devices to make decisions. Due to the limited channel resources, the base station (BS) that connects with an ITS server can only collect data from parts of sensor devices at a time. To improve the number of device associations, we regard vehicle clusters as relays to collect data, which can avoid high capital expenditure and operating expenses from dedicated relays. Due to the frequently varying channel interference and the limited communication coverage of a vehicle cluster relay (VCR), it is challenging to guarantee the transmission rates and the fairness of sensor devices, which will affect the decisions of ITS. For this reason, we propose a Movement- and Fairness-Aware Heuristic (MFAH) algorithm to tackle the above challenges. MFAH sequentially conducts two novel channel allocation schemes, i.e., exclusive channel allocation scheme and compatible channel allocation scheme, to fast allocate channels and improve the channel utilization, which increases the number of device associations while guaranteeing the transmission rates. Regarding the fairness of each device’s associations, we propose a device association scheme based on the cumulative number of device associations and the distance from the target VCR to select appropriate sensor devices to upload data. We theoretically analyze the lower bound of the obtained network utility. Extensive simulations show that compared with benchmarks, the proposed MFAH algorithm converges fast and effectively improves the network utility (i.e., increasing the number of device associations while guaranteeing the fairness of device associations).