Services In Vehicular Networks Research Articles

Traffic and Computation Co-Offloading With Reinforcement Learning in Fog Computing for Industrial Applications

In the past decade, network data communication has experienced a rapid growth, which has led to explosive congestion in heterogeneous networks. Moreover, the emerging industrial applications, such as automatic driving put forward higher requirements on both networks and devices. On the contrary, running computation-intensive industrial applications locally are constrained by the limited resources of devices. Correspondingly, fog computing has recently emerged to reduce the congestion of content-centric networks. It has proven to be a good way in industry and traffic for reducing network delay and processing time. In addition, device-to-device offloading is viewed as a promising paradigm to transmit network data in mobile environment, especially for autodriving vehicles. In this paper, jointly taking both the network traffic and computation workload of industrial traffic into consideration, we explore a fundamental tradeoff between energy consumption and service delay when provisioning mobile services in vehicular networks. In particular, when the available resource in mobile vehicles becomes a bottleneck, we propose a novel model to depict the users' willingness of contributing their resources to the public. We then formulate a cost minimization problem by exploiting the framework of Markov decision progress (MDP) and propose the dynamic reinforcement learning scheduling algorithm and the deep dynamic scheduling algorithm to solve the offloading decision problem. By adopting different mobile trajectory traces, we conduct extensive simulations to evaluate the performance of the proposed algorithms. The results show that our proposed algorithms outperform other benchmark schemes in the mobile edge networks.

An Edge-Assisted Data Distribution Method for Vehicular Network Services

The current data distribution method of vehicular network cannot satisfy the strict spatiotemporal constraints on the transmission of massive service data. Neither can the 5th generation mobile network (5G) meet the massive data demand of vehicular network services. To solve the problems, this paper designs an edge-assisted service data distribution method for vehicular network services. Specifically, the service data distribution was predicted by time series analysis through edge computing, based on the storage capacity of base stations. Then, a spatiotemporal constrained data sharing algorithm was proposed, which sets up a distribution tree to evaluate the importance of each vehicle in data transmission, and heuristically chooses the most important vehicles as seeds to speed up the vehicle-to-vehicle data sharing. Finally, the simulation experiment verifies that our method can greatly reduce the load of 5G network without breaking the spatiotemporal constraints of data transmission in vehicular network.

Traffic Offloading for Online Video Service in Vehicular Networks: A Cooperative Approach

Online video service becomes prevalent nowadays, as people are accustomed to getting information in the form of videos. While home users can easily retrieve all kinds of contents onto their laptops or smartphones, vehicular users are constrained by intermittent connectivity to roadside units (RSUs). Besides, as the load of cellular infrastructure increases dramatically, it is envisioned that the cellular network can be offloaded by utilizing RSUs and vehicular relays. In this paper, we propose a cooperative downloading mechanism in heterogeneous vehicular networks that comprises vehicular ad hoc network and cellular network. In this mechanism, RSUs act as traffic managers to fetch proper data from the Internet and then distribute to vehicles in an approximately optimal manner. Specifically, based on vehicular mobility prediction and internode throughput estimation, a storage time aggregated graph is constructed for planning transmission scheme; then, an iterative greedy-driven algorithm is designed for a suboptimal solution, which has polynomial computational time complexity. Compared with max-throughput and min-delay cooperative downloading (MMCD), simulation results show that our approach outperforms MMCD by $5\%\text{$-$}25\%$ with respect to offload fraction.

Bandwidth Efficiency and Service Adaptiveness Oriented Data Dissemination in Heterogeneous Vehicular Networks

Heterogeneous network resources are expected to cooperate with each other to support efficient data services in vehicular networks. However, current data scheduling methods cannot efficiently exploit the benefit of heterogeneous wireless communication interfaces in vehicular networks. In this paper, we propose a software-defined network based service architecture, which enables the scheduler to manage heterogeneous network resources in a centralized way. We analyze the heterogeneity of both data items and networks in terms of data sizes and network features (e.g., cost, transmission rate, coverage, etc.), respectively. On this basis, we formulate a data broadcast and network interface selection (DBNIS) problem, which aims to minimize both the service delay and the network access cost. To tackle the problem efficiently, we propose a coding-assisted multiobjective evolutionary algorithm (CMOEA), which consists of two components: packet encoding and network interface selection. Specifically, for packet encoding, we first develop a packet-size based random linear encoding (PRLE) technique to improve bandwidth efficiency. Then, we theoretically analyze the performance bound of PRLE. For network interface selection, we propose a multiobjective algorithm for network interface selection to adaptively satisfy dynamic requirements with respect to service delay and network access cost by deriving a set of pareto-solutions. Finally, we build the simulation model and implement CMOEA for performance evaluation. The comprehensive simulation results demonstrate the superiority of CMOEA under a wide range of scenarios.

Secure and Lightweight Cloud-Assisted Video Reporting Protocol over 5G-Enabled Vehicular Networks.

In the vehicular networks, the real-time video reporting service is used to send the recorded videos in the vehicle to the cloud. However, when facilitating the real-time video reporting service in the vehicular networks, the usage of the fourth generation (4G) long term evolution (LTE) was proved to suffer from latency while the IEEE 802.11p standard does not offer sufficient scalability for a such congested environment. To overcome those drawbacks, the fifth-generation (5G)-enabled vehicular network is considered as a promising technology for empowering the real-time video reporting service. In this paper, we note that security and privacy related issues should also be carefully addressed to boost the early adoption of 5G-enabled vehicular networks. There exist a few research works for secure video reporting service in 5G-enabled vehicular networks. However, their usage is limited because of public key certificates and expensive pairing operations. Thus, we propose a secure and lightweight protocol for cloud-assisted video reporting service in 5G-enabled vehicular networks. Compared to the conventional public key certificates, the proposed protocol achieves entities’ authorization through anonymous credential. Also, by using lightweight security primitives instead of expensive bilinear pairing operations, the proposed protocol minimizes the computational overhead. From the evaluation results, we show that the proposed protocol takes the smaller computation and communication time for the cryptographic primitives than that of the well-known Eiza-Ni-Shi protocol.

Adaptive scheduling for real-time and temporal information services in vehicular networks

Vehicular networks represent a research area of significant importance in improving the safety, efficiency and sustainability of transportation systems. One of the key research problems in vehicular networks is real-time data dissemination, which is crucial to the satisfactory performance of many emergent applications providing real-time information services in vehicular networks. Specifically, the two issues need to be addressed in this problem are maintenance of temporal data freshness and timely dissemination of data. Most existing works only considered periodical data update via backbone wired networks in maintaining temporal data freshness. However, many applications rely on passing vehicles to upload their collected information via wireless network, which imposes new challenges as the uplink data update will have to compete with the downlink data dissemination for the limited wireless bandwidth. With such observations, we propose a temporal information service system, in which vehicles are able to collect up-to-date temporal information and upload them to the roadside units (RSU) along their trajectories. Meanwhile, RSU can disseminate its available data items to vehicles based on their specific requests. Particularly, in this paper, we first quantitatively analyze the freshness of temporal data and propose a mathematical model to evaluate the usefulness of the temporal data. Next, we give the formulation of the proposed real-time and temporal information service (RTIS) problem, and prove the NP-hardness of this problem by constructing a polynomial-time reduction from 0–1 knapsack problem. Subsequently, we establish a probabilistic model to theoretically analyze the tradeoff between timely temporal data update and requested data dissemination sharing a common communication resource, which provides a deeper insight of the proposed RTIS. Further, a heuristic algorithm, namely adaptive update request scheduling (AURS), is designed to enhance the efficacy of RTIS by synthesizing the broadcast effect, the real-time service requirement and the service quality in making scheduling decisions. The computational complexity and scalability analysis of AURS is also discussed. Last but not least, a simulation model is implemented and a comprehensive performance evaluation has been carried out to demonstrate the superiority of ARUS against several state-of-the-art approaches in a variety of application scenarios.

Leveraging In-Network Caching in Vehicular Network for Content Distribution

Information-Centric Networking advocates ubiquitous in-network caching to enhance content distribution. Nonsafety application in vehicular communications is emerging beyond the initial safety application. However, content distribution based on TCP/IP Internet service in vehicular networks suffers from typical issue of low delivery ratio in urban environments, where high buildings block or attenuate the radio propagation as well as short radio coverage range. In order to solve this issue to deliver proximity marketing files, in this paper we propose in-network caching scheme in vehicular networks in accordance with traffic features, in which every vehicle is treated as either a subscriber to request a file or as a cache node to supply other nodes so as to accelerate file transmission effectively. Cache strategy of leave copy everywhere is uncoordinated and distributed, which fits the random and dynamic vehicular network. The performance evaluation is carried out by comparing the proposed scheme with the legacy solution of TCP/IP based scheme using simulation tools of OMNeT++ and Veins and SUMO, which is supplied with real-world urban map associated with random but reasonable traffic routes generated by our designed software for every vehicle. The simulation results validate the proposed scheme in four aspects: robustness resisting obstacle buildings, reliability and scalability in different traffic loads, low utilization ratios of RSUs and Internet resource, and efficiency of cache functions.

Channel Allocation for Adaptive Video Streaming in Vehicular Networks

Video services in vehicular networks play an important role in future intelligent transportation systems and vehicular infotainment systems. Yet, at the presence of other services with high priorities, the remaining radio resources for video services are highly dynamic. To support video service of multiple vehicles in vehicular networks, we propose a joint channel allocation and adaptive video streaming algorithm that makes the vehicles compete for channel access opportunities and to request video data with a proper visual quality according to their utilities. A vehicle's request is determined by taking several key factors into consideration, including the location and the velocity of the vehicle, the activity of the high-priority services, the intensity of the competition among multiple vehicles, and the smoothness requirement of visual quality. Simulation results show that the proposed algorithm is superior to the existing algorithms in both interruption ratio and visual quality.

CMTG: A Content-Based Mobile Tendency Geocast Routing Protocol in Urban Vehicular Networks

Efficient dissemination of messages is a vital solution to the vehicular communications and applications. Geocast, delivering messages to a few specific areas, has become an important issue with the accelerating development of the location-based services in vehicular networks. Different from the conventional geocast schemes focusing on the static target areas, in this paper, we propose a content-based mobile tendency geocast (CMTG) routing protocol for urban vehicular networks from the delay tolerant networks (DTNs) perspective to better deal with the high mobility and transient connectivity issues. The target roads of dissemination depend on the preferred tendency and path of message, based on the determination to the message's expected propagating roads. And vehicle decides whether to relay the messages carried to other encountered vehicles by calculating the mobile tendency to the source location of message. The robustness and adaptability of protocol are also proved theoretically. Extensive performance comparisons with other protocols are conducted to show the advantages of CMTG.

Design and Evaluation of Context-Aware and Location-Based Service Discovery Protocols for Vehicular Networks

The increasing number of potential applications related to intelligent transportation systems (ITSs) have attracted researchers to the area of vehicular networks (VNs). Two main classes of applications have lately gained popularity, i.e., security and safety, and traffic information and service location applications. However, several open research challenges are delaying the efficient and widespread deployment and management of such applications in VNs. One of these challenges comprises how vehicles and service providers could discover each other in VNs, which are well known for their large scale and high mobility. Most service discovery strategies available present high overhead and poor performance in a VN environment. Existing context-aware and location-based service discovery protocols (LocVSDPs) are either designed without considering the particularities of VNs or are not scalable with the increase in network density and the number of requests. In this paper, we propose a new context-aware and LocVSDP (EB-LocVSDP) for VNs and its variant (Naive-LocVSDP). Our protocols offer a scalable framework for the discovery of time-sensitive and location-based services in VNs. They rely on a cluster-based infrastructure. Furthermore, LocVSDPs are integrated into the network layer and use channel diversity to improve service discovery efficiency. We discuss the implementation of our protocols and techniques, report on performance evaluation experiments, and offer a comparison against an existing location-based discovery protocol [the Vehicular Information Transfer Protocol (VITP)]. Our simulation results indicate that our proposed LocVSDPs show a gain of 20% in terms of success rate. LocVSDPs use at least 90% less bandwidth than VITP, and their average response time is at least 10% lower than VITP for successful query transactions.

Inter‐domain handover scheme using an intermediate mobile access gateway for seamless service in vehicular networks

AbstractCurrent IP‐level mobility management protocols are unable to satisfy the stringent handover latency requirements for supporting real‐time multimedia services between different domains in a high‐speed vehicular environment. This paper proposes an inter‐domain handover scheme for Proxy Mobile IPv6 (PMIPv6) with a new network entity, called intermediate‐mobile access gateway (iMAG). The iMAG is located between the home and the foreign domains and is connected to both domains. The proposed scheme is a proactive handover approach that performs the inter‐domain L3 handover in advance before the inter‐domain L2 handover while the Mobile Node (MN) is still connected to the iMAG in the home domain. Therefore, the proposed scheme enables the inter‐domain handover latency to reduce as low as the intra‐domain handover latency. Numerical analysis and simulation results demonstrate that the proposed scheme is able to support seamless service continuity in inter‐domain handovers. Copyright © 2009 John Wiley & Sons, Ltd.

MoPADS: A Mobility Profile Aided File Downloading Service in Vehicular Networks

This paper proposes a new intelligent transportation system (ITS) that uses not only integrated cellular and wireless multihop relaying technologies but vehicles' mobility profiles to provide quality yet affordable services as well. It focuses on a subsystem where cellular bandwidth is mostly used for control signals, and a wireless mesh network called ad hoc distribution network (ADN) is used for file transfer in a multihop fashion from one or more server stations to vehicles via access points (APs) using ad hoc channels. A major design goal is to maximize the amount of requested data that can be delivered to the requesting vehicles during their journey using the ADN, taking into consideration the limited coverage of each AP and the requirement that the requested data have to arrive at a certain AP before the requesting vehicles arrive at that AP in order for the data to be downloadable. This paper proves that the optimization problem, as well as its key variations, is NP-hard and proposes efficient solutions to the problem. Analysis and realistic simulations involving a real city map and practical vehicular traces are used to evaluate the performance, and the results indicate that satisfying performance for file download applications can be achieved.