scholarly journals Congestion Game With Link Failures for Network Selection in High-Speed Vehicular Networks

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 76165-76175 ◽  
Author(s):  
Xiaoyun Yan ◽  
Ping Dong ◽  
Xiaojiang Du ◽  
Tao Zheng ◽  
Hongke Zhang ◽  
...  
Keyword(s):  
High Speed ◽  
Vehicular Networks ◽  
Network Selection ◽  
Link Failures ◽  
Congestion Game

scholarly journals Joint optimization of network selection and task offloading for vehicular edge computing

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Lujie Tang ◽  
Bing Tang ◽  
Li Zhang ◽  
Feiyan Guo ◽  
Haiwu He
Keyword(s):  
Large Scale ◽  
Vehicular Networks ◽  
Access Point ◽  
Edge Computing ◽  
Network Selection ◽  
Network Access ◽  
Task Execution ◽  
Point Selection ◽  
Vehicle Movement ◽  
Task Offloading

AbstractTaking the mobile edge computing paradigm as an effective supplement to the vehicular networks can enable vehicles to obtain network resources and computing capability nearby, and meet the current large-scale increase in vehicular service requirements. However, the congestion of wireless networks and insufficient computing resources of edge servers caused by the strong mobility of vehicles and the offloading of a large number of tasks make it difficult to provide users with good quality of service. In existing work, the influence of network access point selection on task execution latency was often not considered. In this paper, a pre-allocation algorithm for vehicle tasks is proposed to solve the problem of service interruption caused by vehicle movement and the limited edge coverage. Then, a system model is utilized to comprehensively consider the vehicle movement characteristics, access point resource utilization, and edge server workloads, so as to characterize the overall latency of vehicle task offloading execution. Furthermore, an adaptive task offloading strategy for automatic and efficient network selection, task offloading decisions in vehicular edge computing is implemented. Experimental results show that the proposed method significantly improves the overall task execution performance and reduces the time overhead of task offloading.

scholarly journals TrustWalker: An Efficient Trust Assessment in Vehicular Internet of Things (VIoT) with Security Consideration

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3945
Author(s):  
Muhammad Sohail ◽  
Rashid Ali ◽  
Muhammad Kashif ◽  
Sher Ali ◽  
Sumet Mehta ◽  
...  
Keyword(s):  
Internet Of Things ◽  
High Speed ◽  
Vehicular Networks ◽  
Information Dissemination ◽  
Search Algorithm ◽  
Modern Technology ◽  
Primary Concern ◽  
On Demand ◽  
Demand Routing ◽  
Route Search

The Internet of Things (IoT) is a world of connected networks and modern technology devices, among them vehicular networks considered more challenging due to high speed and network dynamics. Future trends in IoT allow these inter networks to share information. Also, the previous security solutions to vehicular IoT (VIoT) much emphasize on privacy protection and security related issues using public keys infrastructure. However, the primary concern about efficient trust assessment, authorized users malfunctioning, and secure information dissemination in vehicular wireless networks have not been explored. To cope with these challenges, we propose a trust enhanced on-demand routing (TER) scheme, which adopts TrustWalker (TW) algorithm for efficient trust assessment and route search technique in VIoT. TER comprised of novel three-valued subjective logic (3VSL), TW algorithm, and ad hoc on-demand distance vector (AODV) routing protocol. The simulated results validate the accuracy of the proposed scheme in term of throughput, packet drop ratio (PDR), and end to end (E2E) delay. In the simulation, the execution time of the TW algorithm is analyzed and compared with another route search algorithm, i.e., Assess-Trust (AT), by considering real-world online datasets such as Pretty Good Privacy and Advogato. The accuracy and efficiency of the TW algorithm, even with a large number of vehicle users, are also demonstrated through simulations.

V2V Communication Protocols in Cloud-Assisted Vehicular Networks

2018 ◽  
pp. 125-150
Author(s):  
Amal Ahmed Eltahir ◽  
Rashid A. Saeed
Keyword(s):  
Routing Protocol ◽  
Cellular Network ◽  
High Speed ◽  
Vehicular Networks ◽  
Ad Hoc ◽  
V2v Communication ◽  
Internet Connection ◽  
Wireless Mesh ◽  
Distance Vector ◽  
Aodv Routing Protocol

Integration of vehicular ad-hoc network (VANET) and cellular network is a promising architecture for future machine-to-machine applications. This integration helps the vehicles have steady internet connection through cellular network (i.e., LTE), and at same time communicate with other vehicles. However, dead spot areas and unsuccessful handoff processes due to the high speed of vehicles that can disrupt the implementation of this kind of architecture. In this chapter, simplified cluster-based gateway selection (SCGS) scheme for multi-hop relay in VANET network is proposed. The scheme is achieved by utilizing a new routing protocol called an enhanced hybrid wireless mesh protocol (E-HWMP). The simulations results show that SCGS scheme through E-HWMP protocol performed better than ad-hoc on demand distance vector (AODV) routing protocol. Furthermore, SCGS scheme through E-HWMP is compared with other cluster-based gateway selections used in the previous works; the result shows that SCGS scheme through E-HWMP protocol outperforms the other cluster-based gateway selections schemes.

scholarly journals When 5G Meets Deep Learning: A Systematic Review

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 208
Author(s):  
Guto Leoni Santos ◽  
Patricia Takako Endo ◽  
Djamel Sadok ◽  
Judith Kelner
Keyword(s):  
Systematic Review ◽  
Deep Learning ◽  
High Speed ◽  
Vehicular Networks ◽  
Smart Cities ◽  
The Internet ◽  
Battery Life ◽  
Learning Models ◽  
Broadband Internet ◽  
Main Research

This last decade, the amount of data exchanged on the Internet increased by over a staggering factor of 100, and is expected to exceed well over the 500 exabytes by 2020. This phenomenon is mainly due to the evolution of high-speed broadband Internet and, more specifically, the popularization and wide spread use of smartphones and associated accessible data plans. Although 4G with its long-term evolution (LTE) technology is seen as a mature technology, there is continual improvement to its radio technology and architecture such as in the scope of the LTE Advanced standard, a major enhancement of LTE. However, for the long run, the next generation of telecommunication (5G) is considered and is gaining considerable momentum from both industry and researchers. In addition, with the deployment of the Internet of Things (IoT) applications, smart cities, vehicular networks, e-health systems, and Industry 4.0, a new plethora of 5G services has emerged with very diverging and technologically challenging design requirements. These include high mobile data volume per area, high number of devices connected per area, high data rates, longer battery life for low-power devices, and reduced end-to-end latency. Several technologies are being developed to meet these new requirements, and each of these technologies brings its own design issues and challenges. In this context, deep learning models could be seen as one of the main tools that can be used to process monitoring data and automate decisions. As these models are able to extract relevant features from raw data (images, texts, and other types of unstructured data), the integration between 5G and DL looks promising and one that requires exploring. As main contribution, this paper presents a systematic review about how DL is being applied to solve some 5G issues. Differently from the current literature, we examine data from the last decade and the works that address diverse 5G specific problems, such as physical medium state estimation, network traffic prediction, user device location prediction, self network management, among others. We also discuss the main research challenges when using deep learning models in 5G scenarios and identify several issues that deserve further consideration.

scholarly journals VLC Network Design for High Mobility Users in Urban Tunnels

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 88
Author(s):  
Edmundo Torres-Zapata ◽  
Victor Guerra ◽  
Jose Rabadan ◽  
Martin Luna-Rivera ◽  
Rafael Perez-Jimenez
Keyword(s):  
Network Design ◽  
Intelligent Transportation Systems ◽  
High Speed ◽  
Vehicular Networks ◽  
Low Cost ◽  
High Mobility ◽  
Visible Light Communication ◽  
Transportation Systems ◽  
System Level ◽  
On The Road

Current vehicular systems require real-time information to keep drivers safer and more secure on the road. In addition to the radio frequency (RF) based communication technologies, Visible Light Communication (VLC) has emerged as a complementary way to enable wireless access in intelligent transportation systems (ITS) with a simple design and low-cost deployment. However, integrating VLC in vehicular networks poses some fundamental challenges. In particular, the limited coverage range of the VLC access points and the high speed of vehicles create time-limited links that the existing handover procedures of VLC networks can not be accomplished timely. Therefore, this paper addresses the problem of designing a vehicular VLC network that supports high mobility users. We first modify the traditional VLC network topology to increase uplink reliability. Then, a low-latency handover scheme is proposed to enable mobility in a VLC network. Furthermore, we validate the functionality of the proposed VLC network design method by using system-level simulations of a vehicular tunnel scenario. The analysis and the results show that the proposed method provides a steady connection, where the vehicular node is available more than 99% of the time regardless of the number of vehicular nodes on this network. Additionally, the system is able to achieve a Frame-Error-Rate (FER) performance lower than 10−3.

scholarly journals Mitigating Broadcasting Storm Using Multihead Nomination Clustering in Vehicular Content Centric Networks

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2270
Author(s):  
Ayesha Siddiqa ◽  
Muhammad Diyan ◽  
Muhammad Toaha Raza Khan ◽  
Malik Muhammad Saad ◽  
Dongkyun Kim
Keyword(s):  
High Speed ◽  
Vehicular Networks ◽  
Communication Delay ◽  
Mobile Nodes ◽  
Communication Links ◽  
Vehicle Mobility ◽  
Storm Effect ◽  
Handover Process ◽  
Vehicle Information ◽  
Content Centric Network

Vehicles are highly mobile nodes; therefore, they frequently change their topology. To maintain a stable connection with the server in high-speed vehicular networks, the handover process is restarted again to satisfy the content requests. To satisfy the requested content, a vehicular-content-centric network (VCCN) is proposed. The proposed scheme adopts in-network caching instead of destination-based routing to satisfy the requests. In this regard, various routing protocols have been proposed to increase the communication efficiency of VCCN. Despite disruptive communication links due to head vehicle mobility, the vehicles create a broadcasting storm that increases communication delay and packet drop fraction. To address the issues mentioned above in the VCCN, we proposed a multihead nomination clustering scheme. It extends the hello packet header to get the vehicle information from the cluster vehicles. The novel cluster information table (CIT) has been proposed to maintain several nominated head vehicles of a cluster on roadside units (RSUs). In disruptive communication links due to the head vehicle’s mobility, the RSU nominates the new head vehicle using CIT entries, resulting in the elimination of the broadcasting storm effect on disruptive communication links. Finally, the proposed scheme increases the successful communication rate, decreases the communication delay, and ensures a high cache success ratio on an increasing number of vehicles.

A Fast Cloud-Based Network Selection Scheme Using Coalition Formation Games in Vehicular Networks

2015 ◽  
Vol 64 (11) ◽  
pp. 5327-5339 ◽  
Author(s):  
Ke Xu ◽  
Kuang-Ching Wang ◽  
Rahul Amin ◽  
Jim Martin ◽  
Ryan Izard
Keyword(s):  
Coalition Formation ◽  
Vehicular Networks ◽  
Network Selection ◽  
Selection Scheme

scholarly journals A Spectrum Handoff Scheme for Optimal Network Selection in NEMO Based Cognitive Radio Vehicular Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Krishan Kumar ◽  
Arun Prakash ◽  
Rajeev Tripathi
Keyword(s):  
Cognitive Radio ◽  
Vehicular Networks ◽  
Mobile Network ◽  
Network Selection ◽  
Spectrum Handoff ◽  
Radio Access ◽  
Optimal Network ◽  
Multiple Attributes ◽  
Grey Relational ◽  
Multiple Attributes Decision Making

When a mobile network changes its point of attachments in Cognitive Radio (CR) vehicular networks, the Mobile Router (MR) requires spectrum handoff. Network Mobility (NEMO) in CR vehicular networks is concerned with the management of this movement. In future NEMO based CR vehicular networks deployment, multiple radio access networks may coexist in the overlapping areas having different characteristics in terms of multiple attributes. The CR vehicular node may have the capability to make call for two or more types of nonsafety services such as voice, video, and best effort simultaneously. Hence, it becomes difficult for MR to select optimal network for the spectrum handoff. This can be done by performing spectrum handoff using Multiple Attributes Decision Making (MADM) methods which is the objective of the paper. The MADM methods such as grey relational analysis and cost based methods are used. The application of MADM methods provides wider and optimum choice among the available networks with quality of service. Numerical results reveal that the proposed scheme is effective for spectrum handoff decision for optimal network selection with reduced complexity in NEMO based CR vehicular networks.

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