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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...
Contexts in source publication
Context 1
... simulation parameters in this article are listed in Table 1. In our simulation, the transmission time is divided into time slots with the duration of Dt = 1 s, and each simulation will last 500 time slots. ...
Context 2
... then conduct simulations with more time slots. In the rest of the simulations, we adopt the simulation settings in Table 1. The optimal solution cannot be compared with, because when the amount of total time slots is large enough, the computational load could exceed our computational capacity. Figure 4 shows the influence of arrival rate on the total utility. ...
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Citations
... Our simulation also takes into account communications factors and hence, the most relevant fixed parameters considered for the simulation environment are provided in Table 3, [10], [9], [48], [49], [50]. ...
The concept of the “connected car” offers the potential for safer, more enjoyable and more efficient driving and eventually autonomous driving. However, in urban Vehicular Networks (VNs) , the high mobility of vehicles along roads poses major challenges to the routing protocols needed for a reliable and flexible vehicular communications system. Thus, urban VNs rely on static Road-Side-Units (RSUs) to forward data and to extend coverage across the network. In this paper, we first propose a new Q-learning-based routing algorithm, namely Infrastructure-aided Traffic-Aware Routing (I-TAR), which leverages the static wired RSU infrastructure for packet forwarding. Then, we focus on the multi-source, multi-destination problem and the effect this imposes on node availability, as nodes also participate in other communications paths. This motivates our new hybrid approach, namely Hybrid Infrastructure-aided Traffic Aware Routing (HITAR)
that aims to select the best Vehicle-to-Vehicle/Infrastructure (V2V/I) route. Our findings demonstrate that I-TAR can achieve up to 19% higher average packet-delivery-ratio (APDR) compared to the state-of-the-art. Under a more realistic scenario, where node availability is considered, a decline of up to 51% in APDR performance is observed, whereas the proposed HI-TAR in turn can increase the APDR performance by up to 50% compared to both I-TAR and the state-of-the-art. Finally, when multiple source destination vehicle pairs are considered, all the schemes that model and consider node availability, i.e. limited-availability, achieve from 72.2% to 82.3% lower APDR, when compared to those that do not, i.e. assuming full-availability. However, HI-TAR still provides 34.6% better APDR performance than I-TAR, and ∼40% more than the state-of-the-art.
In Vehicular Networks (VANETs), the rapid movement of vehicles leads to highly time-varying network topology and brings the problem of blind spots in signal coverage. To address these issues, drones are employed to assist data dissemination in VANETs attribute to the flexible development of drones. As random data transmission will result in decreased network performance and low efficiency in data retrieval service, it is urgent to develop efficient data scheduling schemes that meet the quality of service (QoS) of different applications in VANETs. In this context, to fulfill the request of real-time and reliable data transmission, we formulate a data scheduling problem that considers the factors such as priority of data transmission, link quality, link connection time and network fairness. Our goal is to reduce random data transmission, therefore maximizing network transmission utility. We utilize graph theory to describe network topology, in which vehicles and drones are represented as vertices and links between the nodes are represented as edges. The weight of edges indicates the utility obtained when data transmits between the corresponding nodes. We reduce the data scheduling problem to the maximum weighted matching problem and then propose a data scheduling scheme that can satisfy data requests of different vehicles to the maximum extent. The theoretical analysis derives the scheduling algorithm’s time complexity and the number of scheduling stages required to satisfy the data requests. Finally, simulation verifies the proposed scheme’s effectiveness in terms of service rate, service delay, fairness and throughput.
In intelligent transportation systems (ITS), the vehicular ad-hoc network (VANET) is an enabling technology that can provide information exchange services among connected and autonomous vehicles (CAVs). Video streaming over VANETs is a potential application to ensure the safety of drivers and passengers and improve infotainment services. However, owing to the dynamic network topology, video transmission in VANETs is very challenging in terms of latency, reliability, and security. Therefore, a comprehensive summary of the state-of-art video streaming over VANETs is surveyed in this work. Firstly, related works and background knowledge are introduced. Then, a systematic survey on resource allocation (RA) scheme for video streaming in VANETs is provided, and some prevailing and feasible optimization tools are elaborated. Furthermore, enabling technologies of video streaming over VANETs are summarized with a special focus on the integration of video communication, caching, and computing. Finally, we give some challenges and future research directions.
