Abstract
Internet of Vehicles has become a promising way to realize the evolution from vehicular ad hoc networks and next-generation intelligent transportation system into future autonomous driving scenarios, clean-energy intelligent vehicles, and Smart Cities. However, multicasting service messages on available service channels and periodic exchanges of beacon messages on control channel cause the problem of efficiently scheduling those messages via multichannel transmission for intelligent vehicle terminal, to support real-world applications in Internet of Vehicles scenario. In this article, we investigate the intelligent vehicle terminal architecture and, particularly, design the wireless communication board by incorporating multicasting and congestion control modules. Especially, we present a multicast data delivery scheme with random-delay lowest-cost constraint to transfer service messages on service channels. Furthermore, a priority-aware congestion control scheme is also proposed by considering differentiated priorities of beacon messages on control channel, to cope with the congestion problem at bottleneck vehicle node. Based on the proposed schemes, we build up the RanLow (Random-delay Lowest-cost) module and the priority-aware congestion control (PARCEL) module by enabling multicasting and congestion control together in wireless communication board of the intelligent vehicle terminal architecture. Finally, the experimental results and comparison show that our devised RanLow module and PARCEL module are feasible and more efficient than existing schemes.
Highlights
Due to the limited number of destination vehicle nodes in our experiments, we provide simulation results to evaluate the performance of the RanLow on the same setting of experiment parameters as shown module under multicast data delivery (MDD) scheme with randomdelay lowest-cost (RDLC) constraint by in Table 3, we intend to randomly deploy various numcomparing with the constrained Dijkstra heuristic (CDKS) and KPP strategies
Aiming to compare with the priority-aware congestion control (PARCEL) module under the PARCEL scheme, when aggregated data load exceeds available capacity of the buffer of congested vehicle node, we consider the existing classical congestion control strategies including:[36,37] (a) drop front (DF), wherein the beacon message with longest queuing time in the buffer is dropped; (b) drop last (DL), wherein the last beacon message received in the buffer is dropped; (c) drop oldest (DO), wherein the beacon message in the buffer with the smallest remaining time-to-live (TTL) is dropped
We studied how to deal with multicasting service messages on service channels (SCHs) along with periodic exchanges of beacon messages on control channel (CCH) for Internet of Vehicles (IoV) scenario
Summary
International Journal of Distributed Sensor Networks information platforms.[2] Compared with traditional intelligent transportation system (ITS), IoV puts more emphasis on expanding interactions and connections among vehicles, drivers, passengers, and RSUs, aiming to accommodate for fifth generation (5G)-enabled vehicular networks.[4] To this end, the primary goal of IoV is to make drivers obtain the real-time road traffic information to improve the road safety for drivers, to provide passengers with the travel convenience and comfort, to enjoy the existing Internet-based services (e.g. video conference, gaming, content sharing, and Web surfing), and to further benefit from big data applications through fog computing.[5,6,7] In addition, IoV can be deemed to a superset of vehicular ad hoc networks (VANETs). It goes without saying that IoV has become a promising way to realize the evolution from VANETs and next-generation ITS into future autonomous driving scenarios,[7] clean-energy intelligent vehicles,[8] and Smart Cities.[9]
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