Utility maximization for multi-vehicle multimedia dissemination in vehicular ad hoc networks. (October 2018)

• Record Type: Journal Article
• Authors: Pan, Bin; Wu, Hao
• Is Part Of: International journal of distributed sensor networks. Volume 14:Number 10(2018)
• Publication Date: 2018-10
• Subjects: Multi-vehicle -- multimedia dissemination -- vehicle-to-infrastructure communication -- utility maximization -- vehicular ad hoc networks; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147718806717
• Languages: English
• ISSNs: 1550-1329

Abstract

In vehicular ad hoc networks, maximizing the satisfaction level of multimedia services is a significant issue of concern to users. Relying on the vehicle-to-infrastructure communications, how to schedule the disseminations of multiple vehicles for ensuring high efficiency and guarantee users' quality of service is difficult and challenging, due to the limited channel resource and vehicle sojourn time. In this article, the scheduling problem of multi-vehicle multimedia dissemination in vehicular ad hoc networks is investigated. A utility model is developed to map the throughput (i.e. the amount of received data) to the user satisfaction level. The scheduling problem is formulated as a utility maximization problem of all the users, which is NP-hard. Then it is transformed into a finite-state decision problem and we obtained an optimal solution by the searching algorithm, which is impractical and can serve as the upper bound. To solve the problem in practice, an online admission control and scheduling algorithm is devised, which guarantees the inflexible data requirements of those admitted vehicles and maximize the total utility. Finally, we implement and conduct extensive simulations on the basis of real video trace to evaluate the performance. Simulation results show that our proposed algorithm has better performance than the state-of-the-art and the conventional algorithms. Thus, it can effectively make scheduling decisions to obtain higher total utility and admission probability.