Special Issue "Vehicular Networks and Communications"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 31 January 2020

Special Issue Editors

Guest Editor
Dr. Omprakash Kaiwartya

School of Science and Technology, Nottingham Trent University, Clifton Campus, Nottingham NG11 8NS, UK
Website | E-Mail
Fax: +44 (0)115 84 83567
Interests: green computing; Internet of Things; wireless sensor networks; Internet of connected vehicles; heterogeneous networking; electronic vehicles
Guest Editor
Dr. Zhengguo Sheng

Department of Engineering and Design, University of Sussex, BN1 9RH, UK
Website | E-Mail
Interests: vehicular communications, IoT, wireless communications and networking
Guest Editor
Prof. Wei-Chang Yeh

Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Taiwan
Website | E-Mail
Interests: Algorithms Design, Optimization, and Soft Computing Techniques
Guest Editor
Prof. Qian Fu

School of Power Engineering, Chongqing University, Chongqing 400030, China
Website | E-Mail
Interests: Energy Saving, Fuel Cell, Micro Systems

Special Issue Information

Dear Colleagues,

Vehicular networks have the potential to address most traffic-related issues ranging from traffic jams and accidents, to pollution control and traffic management. This is possible by the effective utilization of accurate traffic prediction, and cooperative traffic information sharing over vehicular networks. Due to the recent advances in sensor and communication technologies, vehicular networks are transforming towards the Internet of Connected Vehicles (IoV). Due to the enabling technologies for heterogeneous vehicular communications, including Vehicle-to-Vehicle (V2V), Vehicle-to-Roadside unit (V2R), Vehicle-to-Personal Devices (V2P), Vehicle-to-Mobile-Infrastructure (V2I), and Vehicle-to-Sensor (V2S) communications. In order to enable a Vehicle-to-Everything (V2X)-centric IoV framework, various technical questions need to be addressed, focusing on the quality of service in heterogeneous wireless communication environments.

You are welcome to submit an unpublished original research work related to the theme of ‘Vehicular Networks and Communications’ in sensor-enabled communication network environments. 

Dr. Omprakash Kaiwartya
Dr. Zhengguo Sheng
Prof. Wei-Chang Yeh
Prof. Qian Fu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • V2X communications, V2V, V2R, V2P, V2I, V2S
  • Routing, Data Dissemination, Data Aggregation, Path Section, Optimization
  • Medium Access Protocols, Congestion Control, Prioritization Techniques
  • Green Computing, Energy Consumption, Energy Harvesting, Lifetime Maximixation.
  • Secure Communication, Security Optimization, Distibuted Security,
  • Privacy Preservation, Privacy Loss, Secrate Communication,
  • Vedio Transmission, Vedio Encoding/Decoding, Vedio Compression,
  • Edge Computing, Fog Computing, Cloud Computing, Distributed Computing,
  • Localization, Geographic, GPS outage, GPS free, GPS assisted
  • Propagation Modelling, Interference, Path Loss Modelling

Published Papers (6 papers)

View options order results:
result details:
Displaying articles 1-6
Export citation of selected articles as:

Research

Jump to: Review

Open AccessArticle
Fuzzy System and Time Window Applied to Traffic Service Network Problems under a Multi-Demand Random Network
Electronics 2019, 8(5), 539; https://doi.org/10.3390/electronics8050539
Received: 19 April 2019 / Revised: 9 May 2019 / Accepted: 10 May 2019 / Published: 13 May 2019
PDF Full-text (979 KB)
Abstract
The transportation network promotes key human development links such as social production, population movement and resource exchange. As cities continue to expand, transportation networks become increasingly complex. A bad traffic network design will affect the quality of urban development and cause regional economic [...] Read more.
The transportation network promotes key human development links such as social production, population movement and resource exchange. As cities continue to expand, transportation networks become increasingly complex. A bad traffic network design will affect the quality of urban development and cause regional economic losses. How to plan transportation routes and allocate transportation resources is an important issue in today’s society. This study uses the network reliability method to solve traffic network problems. Network reliability refers to the probability of a successful connection between the source and sink nodes in the network. There are many systems in the world that use network architecture; therefore, network reliability is widely used in various practical problems and cases. In the past, some scholars have used network reliability to solve traffic service network problems. However, the processing of time is not detailed enough to fully express the real user’s time requirements and does not consider that the route traffic will affect the reliability of the entire network. This study improves on past network reliability methods by using a fuzzy system and a time window to construct a network model. Using the concept of fuzzy systems, according to past experience, data or expert predictions to define the degree of flow, time and reliability, can also determine the relationship between these factors. The time window can be adjusted according to the time limit in reality, reaching the limit of the complete expression time. In addition, the network reliability algorithm used in this study is a direct algorithm. Compared with the past indirect algorithms, the computation time is greatly reduced and complex problems can be solved more efficiently. Full article
(This article belongs to the Special Issue Vehicular Networks and Communications)
Open AccessArticle
Enabling Green Wireless Sensor Networks: Energy Efficient T-MAC Using Markov Chain Based Optimization
Electronics 2019, 8(5), 534; https://doi.org/10.3390/electronics8050534
Received: 18 April 2019 / Revised: 5 May 2019 / Accepted: 8 May 2019 / Published: 13 May 2019
PDF Full-text (1854 KB) | HTML Full-text | XML Full-text
Abstract
Due to the rapidly growing sensor-enabled connected world around us, with the continuously decreasing size of sensors from smaller to tiny, energy efficiency in wireless sensor networks has drawn ample consideration in both academia as well as in industries’ R&D. The literature of [...] Read more.
Due to the rapidly growing sensor-enabled connected world around us, with the continuously decreasing size of sensors from smaller to tiny, energy efficiency in wireless sensor networks has drawn ample consideration in both academia as well as in industries’ R&D. The literature of energy efficiency in wireless sensor networks (WSNs) is focused on the three layers of wireless communication, namely the physical, Medium Access Control (MAC) and network layers. Physical layer-centric energy efficiency techniques have limited capabilities due to hardware designs and size considerations. Network layer-centric energy efficiency approaches have been constrained, in view of network dynamics and available network infrastructures. However, energy efficiency at the MAC layer requires a traffic cooperative transmission control. In this context, this paper presents a one-dimensional discrete-time Markov chain analytical model of the Timeout Medium Access Control (T-MAC) protocol. Specifically, an analytical model is derived for T-MAC focusing on an analysis of service delay, throughput, energy consumption and power efficiency under unsaturated traffic conditions. The service delay model calculates the average service delay using the adaptive sleep wakeup schedules. The component models include a queuing theory-based throughput analysis model, a cycle probability-based analytical model for computing the probabilities of a successful transmission, collision, and the idle state of a sensor, as well as an energy consumption model for the sensor’s life cycle. A fair performance assessment of the proposed T-MAC analytical model attests to the energy efficiency of the model when compared to that of state-of-the-art techniques, in terms of better power saving, a higher throughput and a lower energy consumption under various traffic loads. Full article
(This article belongs to the Special Issue Vehicular Networks and Communications)
Figures

Figure 1

Open AccessArticle
Secure Intelligent Vehicular Network Using Fog Computing
Electronics 2019, 8(4), 455; https://doi.org/10.3390/electronics8040455
Received: 16 February 2019 / Revised: 16 April 2019 / Accepted: 18 April 2019 / Published: 24 April 2019
PDF Full-text (2900 KB) | HTML Full-text | XML Full-text
Abstract
VANET (vehicular ad hoc network) has a main objective to improve driver safety and traffic efficiency. The intermittent exchange of real-time safety message delivery in VANET has become an urgent concern due to DoS (denial of service) and smart and normal intrusions (SNI) [...] Read more.
VANET (vehicular ad hoc network) has a main objective to improve driver safety and traffic efficiency. The intermittent exchange of real-time safety message delivery in VANET has become an urgent concern due to DoS (denial of service) and smart and normal intrusions (SNI) attacks. The intermittent communication of VANET generates huge amount of data which requires typical storage and intelligence infrastructure. Fog computing (FC) plays an important role in storage, computation, and communication needs. In this research, fog computing (FC) integrates with hybrid optimization algorithms (OAs) including the Cuckoo search algorithm (CSA), firefly algorithm (FA), firefly neural network, and the key distribution establishment (KDE) for authenticating both the network level and the node level against all attacks for trustworthiness in VANET. The proposed scheme is termed “Secure Intelligent Vehicular Network using fog computing” (SIVNFC). A feedforward back propagation neural network (FFBP-NN), also termed the firefly neural, is used as a classifier to distinguish between the attacking vehicles and genuine vehicles. The SIVNFC scheme is compared with the Cuckoo, the FA, and the firefly neural network to evaluate the quality of services (QoS) parameters such as jitter and throughput. Full article
(This article belongs to the Special Issue Vehicular Networks and Communications)
Figures

Figure 1

Open AccessArticle
Green Computing in Sensors-Enabled Internet of Things: Neuro Fuzzy Logic-Based Load Balancing
Electronics 2019, 8(4), 384; https://doi.org/10.3390/electronics8040384
Received: 1 March 2019 / Revised: 23 March 2019 / Accepted: 25 March 2019 / Published: 29 March 2019
PDF Full-text (2565 KB) | HTML Full-text | XML Full-text
Abstract
Energy is a precious resource in the sensors-enabled Internet of Things (IoT). Unequal load on sensors deplete their energy quickly, which may interrupt the operations in the network. Further, a single artificial intelligence technique is not enough to solve the problem of load [...] Read more.
Energy is a precious resource in the sensors-enabled Internet of Things (IoT). Unequal load on sensors deplete their energy quickly, which may interrupt the operations in the network. Further, a single artificial intelligence technique is not enough to solve the problem of load balancing and minimize energy consumption, because of the integration of ubiquitous smart-sensors-enabled IoT. In this paper, we present an adaptive neuro fuzzy clustering algorithm (ANFCA) to balance the load evenly among sensors. We synthesized fuzzy logic and a neural network to counterbalance the selection of the optimal number of cluster heads and even distribution of load among the sensors. We developed fuzzy rules, sets, and membership functions of an adaptive neuro fuzzy inference system to decide whether a sensor can play the role of a cluster head based on the parameters of residual energy, node distance to the base station, and node density. The proposed ANFCA outperformed the state-of-the-art algorithms in terms of node death rate percentage, number of remaining functioning nodes, average energy consumption, and standard deviation of residual energy. Full article
(This article belongs to the Special Issue Vehicular Networks and Communications)
Figures

Figure 1

Open AccessArticle
Transmission Capacity Characterization in VANETs with Enhanced Distributed Channel Access
Electronics 2019, 8(3), 340; https://doi.org/10.3390/electronics8030340
Received: 14 January 2019 / Revised: 15 March 2019 / Accepted: 15 March 2019 / Published: 20 March 2019
PDF Full-text (3320 KB) | HTML Full-text | XML Full-text
Abstract
The traditional research on the capacity of the Vehicular Ad Hoc Networks (VANETs) mainly lacks realistic models mimicking the behaviors of vehicles and the MAC protocol applied by IEEE 802.11p. To overcome these drawbacks, in this paper, the network transmission capacity analysis for [...] Read more.
The traditional research on the capacity of the Vehicular Ad Hoc Networks (VANETs) mainly lacks realistic models mimicking the behaviors of vehicles and the MAC protocol applied by IEEE 802.11p. To overcome these drawbacks, in this paper, the network transmission capacity analysis for VANETs is carried out from the perspective of the spatial geometric relationship among different vehicles. Specifically, the transmission scheme in this system is set to mimic enhanced distributed channel access (EDCA) protocol, in which the division of priorities is taken into account both the data type and the transmission distance requirement. Meanwhile, the moving pattern of vehicles is described as the classic car-following model according to realistic characteristics of VANET, and the propagation channel is modeled as a combination of large-scale path-loss and small-scale Rayleigh fading. Based on this model, the transmission opportunity under EDCA protocol is quantified and compared with that of CSMA/CA, and then the outage probability is calculated under the worst interfered scenario. Finally, the transmission capacity is thereby calculated and verified by the simulation results. Full article
(This article belongs to the Special Issue Vehicular Networks and Communications)
Figures

Figure 1

Review

Jump to: Research

Open AccessReview
Multi-Layer Problems and Solutions in VANETs: A Review
Electronics 2019, 8(2), 204; https://doi.org/10.3390/electronics8020204
Received: 13 January 2019 / Revised: 5 February 2019 / Accepted: 6 February 2019 / Published: 11 February 2019
PDF Full-text (1332 KB) | HTML Full-text | XML Full-text
Abstract
The Dedicated Short Range Communication (DSRC) technology supports the vehicular communications through Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) Communication, by operating at 5.9 GHz band (U.S. Standard). The Physical (PHY) and Medium Access Control (MAC) Layer are defined by the [...] Read more.
The Dedicated Short Range Communication (DSRC) technology supports the vehicular communications through Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) Communication, by operating at 5.9 GHz band (U.S. Standard). The Physical (PHY) and Medium Access Control (MAC) Layer are defined by the IEEE 802.11p, while the IEEE 1609 family of standards define the Wireless Access in Vehicular Environment (WAVE); a suite of communication and security standards in the Vehicular Area Networks (VANETs). There has been a lot of research regarding several challenges in VANETs, from spectrum utilization to multichannel operation and from routing to security issues. The aim of all is to improve the performance of the network and support scalability in VANETs; which is defined as the ability of the network to handle the addition of vehicles (nodes) without suffering noticeable degradation of performance or administrative overhead. In this paper, we aim to highlight multilayer challenges concerning the performance of the VANETs, the already proposed solutions, and the possible future work. Full article
(This article belongs to the Special Issue Vehicular Networks and Communications)
Figures

Figure 1

Electronics EISSN 2079-9292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top