Joint Data-Prefetching and Broadcast-Scheduling for Hybrid Vehicular Networks

Abstract

Prefetching data at the road side units (RSUs) and transmitting them to interested vehicles can help reduce the traffic load in vehicular networks, and improve the data retrieval time. Most prior work in this area opted for supporting data delivery by using a single data rate, in stark contrast to common networking knowledge that good tradeoffs can be achieved in terms of performance by adopting different, more appropriate data rates for different users. In particular, in general wireless networks it is well known that when the data rate is small, the transmission is robust but takes too long; while when the data rate is high, the data delivery time is smaller but the coverage area of the RSU becomes smaller and so does the robustness. In this paper, we study the joint problem of caching and scheduling to decide, what data to prefetch, when to deliver it, and which data rate to use, with the objective of maximizing the volume of data delivered to the mobile vehicles in the network. This problem is subject to many constraints imposed by the real system limits, such as the mobility pattern of the vehicles, the distribution of data requests by the vehicles, and the limited buffer space available at the RSUs. We formulate the problem as an integer linear programming problem, and propose a heuristic caching algorithm, and a heuristic scheduling algorithm to find an approximate solution that is shown via simulation to improve the throughput, compared to standard alternative approaches.