Keywords

1 Introduction

Traffic management is a well-known global issue due to the increment of vehicles on the road. The movement of vehicles is increasing which led to severe traffic issues in the metro and large cities. Bogota in Columbia topped as the most congested Latin American city with drivers losing 191 h which is nearly 8 days. Indian cities such as Bengaluru, Mumbai, and Delhi are facing the worst traffic congestion in the world with losing 243 h, 209 h, and 190 h, respectively. Drivers in the United States lose 97 h per year due to traffic issues. The lost hours due to traffic issues directly affected fuel wastage, environment, and indirectly affect productivity, economy, and business [1, 2]. Apart from these road traffic accounted for 40% of accidents, 1.3 million casualties, and 20–30 million injuries annually according to the WHO report, 2016. Many countries have developed traffic management systems dealing with signal timing procedures. Timing-based traffic signals controlled by pneumatic actuators are used to control the traffic, yet it could not have adequate control over the heavy traffic scenarios in modern smart cities. It is essential to have better communications and connections within the vehicles as well as surroundings due to their mobility [3].

The enlargement of Information and communication technologies (ICT) is used to extract traffic information and direct the drivers to take traffic less routes. IoT can play a key role by restricting traffic congestion, promoting safety, and coordinating vehicle mobility on the road. IoT has smart sensors, computing devices are interacting together and the ability to receive, process, and transfer data with no human participation [4]. IoT can convert into smart roads by embedding sensory systems and providing information regarding traffic situations. One of the highly attractive applications of IoT in intelligent transportation system (ITS) where traffic management is ensured well by smarter use of transport networks enable safety, route optimization, delay reduction, and pollution control. IoT was introduced in connected vehicles in 1998 applied with radio frequency identification (RFID) sensor tags. Tracking of vehicle mobility, as well as connectivity, becomes more convenient in ITS, after adopting technologies such as global positioning system (GPS), bluetooth, WiFi, Zigbee, and so on [5, 6]. These technologies brought a new environment by communicating between the vehicles as well as controlling vehicle mobility. Vehicular communication systems, such as V2V, V2I, V2P, and vehicle to everything (V2X) allow a vehicle to communicate the circumstances with short-range wireless signals. It can widen the vehicle recognition events aided by smart sensors and detectors to provide necessary guidelines for drivers to take smart and safe decisions. For example, these technologies provide traffic flow parameters, road conditions, short cuts/alternate routes, atmospheric conditions, and so on can be shared by drivers of other connected vehicles developing networks called VANETs [24]. VANET converts all the vehicles as a wireless router or mobile node which takes part in the VANET network, in that way it enables vehicles to be connected inside the network. In case a vehicle moves out of the VANET network, other vehicles can join inside and create a mobile network. VANET is limited with some connected vehicles which cover only a small mobile network. VANET cannot provide sustainable services for broader areas so it is difficult to manage several situations such as heavy traffic jams, larger city areas, driver misbehaviors, complex road networks, and so on. The usage of VANET is local and discrete, temporary and unstable; therefore, usage of VANET is becoming stagnate [7, 8].

Contrary to the VANET network, IoV has brought forth two major technologies such as vehicle networking and vehicle intelligence by integrating communication advancements with connected vehicles. By using techniques such as deep learning, artificial intelligence (AI), cognitive computing, and so on with intelligent integration of humans, vehicles, environment, and things as a whole broader network. IoV is not short and unstable like VANET, but it is an open network system with integrated services that can provide even to a whole country. The benefits of IoV are highly controllable, manageable, operationalized, and credible. IoV network is composed of multiple vehicles, multiple networks, multiple users, and multiple things. IoV can govern and quantify huge complex data with the intention of improving the sustainability of information, communication, and complex network systems [9].

The essential ideology of IoV is to comprehend thoroughly the unification of vehicle–human–environment to nurture efficient transportation, reduce the cost factors, avoid collisions and fatalities, ensure the safety prospects of humans as well as enjoy their rides [10]. VANET is a vehicle interconnection network that can act as a subnetwork of IoV. IoV has another subset that is vehicle Telematics, which can transfer and interchange the electronic data and location-based information between connected vehicles. The information such as remote diagnostics, navigation, entertainment content, and so on comes under Vehicle Telematics, which can align with intelligent transportation systems considered as an application of IoV, for example, traffic guidance system, intelligent vehicle control, safe navigation. VANET, vehicle Telematics, and other connected vehicles have failed to handle global information due to their lack of processing capacity which is limited to short-term applications. The inception of IoT, cloud computing, deep learning, AI, and big data has evolved into IoV, to handle and compute/process global information. IoV has characteristics such as the trajectory of vehicles which is subject to the road distributions of the city, integration of humans and vehicles. Based on the network model, service model and human–vehicle behavior model will be developed. IoV interconnects intelligent systems of vehicles, humans, cyber-physical systems of the surrounding environment and integrates along with sensors, mobile devices into a global network [11,12,13,14,15]. IoV has a combination of inter-vehicular networks, intra-vehicular networks, and vehicular mobile internet. Thus, it is possible to build a global network in IoV, with multilevel collaboration with existing multi-vehicle, multiple users, multiple networks, and multiple things. Sensors are smart devices in IoV, playing a vital role in terms of feeding information and behaving wisely based on the need. IoV has external sensors, internal sensors, and measurable sensors. External sensors primarily providing information on GPS (global positioning system), LIDARs, cameras, and so on. Internal sensors such as automotive sensors (brakes, accelerator, etc.) and cockpit sensors (alertness, the health status of the driver, etc.). Social media, phone texts, tweets will be considered as measurable sensor outputs to understand the state of the driver.

Profitability from connected cars and their drive technology would generate up to 81 million USD income annually. The effective usage of traveling time is the prime goal of IoV. IoV has a potential market opportunity by monetizing the time wasted by traveling in the coming years. Even 5 min saved globally by IoV are expected to generate 25 million Euros per year by 2030. European Union made an initiative to develop next-generation Cooperative Intelligent Transportation Systems (C-ITS). Various reports from the United Kingdom, United States, and Australia suggested the positive impact of connected vehicles. In the United States, security chips were equipped in vehicles to define an identity for every entity and vehicle tracking could be done on the internet. In Delhi, all registered vehicles and metros were installed with GPS and Wireless Fidelity (Wi-Fi). Google is working along with certain automotive industries and IT companies to develop an Android system for connected vehicles; “Carplay” was developed by Apple which enables the driver to access services of iPhone through the display of car with a voice support feature. All such efforts are the roadmap toward the design and development of IoV.

By considering all these facts, the proposed chapter has the following sections. Section 2 provides basic network architecture and its elements of IoV. Section 3 presents four layers (4L), five layers (5L), and seven layers (7L) of IoV architecture and its overview. Various types of communications are also discussed here. Section 4 gives architecture analysis and protocols. Finally, Section 5 brings toward the future direction of IoV and its transformation with conclusions.

2 Network Architecture of IoV

Numerous cycles engaged with network communications in OSI or TCP/IP model like packets directing and bundles conveying. Agreeable C-ITS parts that structure the IoV ecological system depend on numerous components, and they generally include various gadgets or infrastructures. Moreover, being a specific MANETs (Mobile Ad hoc Network) network classification, VANETs, V2I, V2X, and thus IoV sending is unpredictable and needs an unprecedented effort and thought because about their characteristics, for instance, a huge degree of versatility and dynamic change in the geography, which produces dispersed organizations. For example, ETSI in Europe design is portrayed by Fig. 14.1.

Fig. 14.1
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ETSI architecture

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The principal stands out from the conventional TCP/IP or OSI model is:

  • The occupancy of a facilities layer which is liable for VANETs affiliated functions.

  • The blend of the network and transport layer falls under a single layer.

  • Incorporation of two uncommon layers: Management and Security.

  • The occupancy of ITS committed stack which coordinates the geo networking addressing.

Notwithstanding, such designs are just identified with the inward structure and capacities of one gadget engaged with the interchanges without explaining the communication cycle if there should arise an occurrence of handover or different systems that include outside gadgets cooperation. The game plan of IoT in the VANETs setting engaged promising courses of action and applications (for instance, persistent applications for autonomous driving, road traffic the board applications and comfort applications), which were delivered purported as IoV. IoV biological system is essentially shaped by four sections which are:

  • End centers: vehicles, PDAs, sensors, and related contraptions

  • Establishment: Roadside units (RSUs), Wi-Fi hotspots, cell associations (3G/LTE) base stations

  • Activities, for example, methodology prerequisite, stream-based organization, security and assessing and

  • Administrations, for instance, public cloud for enrollment-based organizations, private cloud, attempt cloud for huge business data, voice or video, and so on.

These days, few suitable association structures between these IoV segments are suggested. This offer would like to IoV arrangement probability despite the RSU sending delay since its costly execution, which is assessed to €660 Million from 2020 to 2026. Multiple specifications and normalization exercises in IoV space are still in development, a survey on network design in IoV found that may be of extraordinary significance and will assist the scientists to know and refreshed to what in particular is as of now completed in IoV. This persuades us to commit to the IoV research network.

3 IoV Architectures Overview

As of now, various endeavors and the academic world examiners are giving in-solid thought to novel association plans that could capably permit the IoV sending and associated business market models. In [16], Bonomi from Cisco has depicted 4L-based plans as showed up in Fig. 14.2. The suggested model has four phases that each IoV correspondence reliably incorporates with Embedded systems and sensors, Multiservice Edge, Core, Datacenter, and Cloud, as seen in Fig. 14.2.

Fig. 14.2
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Four layers architecture of IoV

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In [17], authors likewise presented a five-layered engineering, outlined in Fig. 14.3, which is made out of the accompanying layers:

Fig. 14.3
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Five layers architecture of IoV

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  • Perception: The connection between the vehicle and its present condition is depicted in this layer. Devices kept inside the vehicle, for instance, sensors, actuators, singular devices, and those presented over the road, RSU to collect appropriate information to be used in vehicle’s comments.

  • Coordination: this layer is primarily trustworthy on interoperability, controlling, and report transportation security.

  • AI: This is the center layer where choices part undertakings must be executed. This layer predominantly centers around large information examination, information mining, distributed computing, and master frameworks-based choice.

  • Application: This layer concerns such an organization and pre-necessities present in the structure.

  • Business: the part depicts which kind of associations the IoV deface kit will offer to customers.

To propose a solid controlling show for IoV climate [18] designing given in past works, by planning the software-defined networks (SDN) perspective which involves secluding the association traffic light plane and the data transfer plane. Accordingly, the presented architecture with six layers (6L) which are perception layer, correspondence layer, application layer, cost layer, security layer, and a layer for law, ethic, private life, and legal use. The SDN perspective is applied in the correspondence layer in which they decide an SDN steering convention (Control plane + Data plane) sub-layer and radio access technologies (RAT) types (homogenous or heterogeneous) sub-layer [19].

In [20], the authors proposed a 7L-based design, which showed up in Fig. 14.4. They arranged this 7L plan by decreasing the layers functionalities’ multifaceted nature and by social event the essentially equivalent to limits in same and fitting layers, as needs are, making straightforward its utilization.

Fig. 14.4
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Seven layers architecture of IoV

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The principle goal of this design is the enhancement of the number of layers by upgrading the differentiability among layers. This enhancement must be additionally sent as much productively as conceivable to accomplish the organization qualities and necessities which are mostly: interoperability, dependability, versatility, particularity, straightforwardness, and combination adaptability with the internet. As it is mentioned in Fig. 14.4, a layer for customer collaboration which exchanges with the UI, a layer for data making sure about, a pre-taking care of layer in which assembled data must be pre-arranged before employed in the correspondence layer, which encourages the heterogeneous organization surroundings. From that point forward, they incorporate a layer for interoperability and organization specialist providers which are called management. At long last, they recommended a business layer and a security-related layer.

They additionally acquaint a gadget with gadget (D2D) correspondence approach which may be an encouraging and presumably utilized arrangement in the following years in machine to machine (M2M) interchanges setting.

An altogether and comprehensive audit on the gadget to gadget correspondences can be discovered in [21]. The D2D design approach in IoV is represented in Fig. 14.5. Considering the moving issue toward asset distribution to assure Real-time (RT) traffic in IoV and to update the asset utilization capability, creators of [22], determined an IOV design, regardless, they moreover suggested a model for asset allotment and improvement by following the effortlessly and solicitation approach and utility limit. The recommended plan is a different leveled IoV designing that involves three layers which are: a data gathering cloud, a web-access cloud, application cloud. In their architecture, they additionally thought to be four organizations which are: The on-vehicle Sensor (OVS) organization, V2Vorganization, close to street V2I organization, and a V2P organization.

Fig. 14.5
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Different types of D2D communications

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Authors of [23] presented a fog enlisting RT-Based ITS Big Data Analytics (RITS-BDA) designing in IoV conditions, which is made out of a three-estimation structure configuration including the components of IoV, smart figuring, and consistent huge data assessment. RITS-BDA is then multi-dimensional layered designing which is made of the going with layers: 4L in the astute enrolling estimation (three various leveled Fog figuring layers, circulated processing layer), three layers (3L) for the progressing enormous data assessment estimation (serving layer, group layer, speed layer), and 6L for IoV estimation. Their designing way to provide the real execution of persistent ITS colossal data applications and is loosened up from a nonexclusive consistent enormous data getting ready to plan considered lambda designing that was introduced in [24].

4 Protocols Stack and Architecture Analysis of IoV

A conventional stack is given for every design which contains particular of the utilitarian demands of each plan layer by figuring out the proper existing shows. For example, VANETs standards, 3GPP rules, and so on. For the 5L design [17], a convention stack (shown in Fig. 14.6) is formed by four planes which are:

Fig. 14.6
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Protocol stack of the IoV architecture with five layers

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The board plane, activity plane, security plane, and layer plane. In any case, [21] proposed a show store of two planes: an operational plane and a security plane appeared in Fig. 14.7.

Fig. 14.7
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IoV Protocol stack with seven layers

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CALM-SL = CALM Service Layer

OMA-DM = Open Mobile Alliance Device Management

6LoWPAN = IPv6 over Low-Power Wireless Personal Area Networks

RPL = Routing Protocol for Low-Power and Lossy Networks

IP = Internet Protocol

ROLL = Routing Over Low Power and Lossy Networks

XMPP = Extensible Messaging and Presence Protocol

CoAP = Constrained Application Protocol

HTTP REST = Hypertext Transfer Protocol Representational State Transfer

MQTT = Message Queuing Telemetry Transport

LLAP = Lightweight Logical Automation Protocol

LoRaWAN = Low-Power Wide Area Network

OTrP = Open Trust Protocol

S-MIB = Security Management Information Base

HSM = Hardware Security Module

S-IC = Security Information Connector

The coordination calculation control layer is utilized for acknowledging processing and control on human, vehicle, climate equivalently. It can control single and multitude through registering singular data coordinately. Besides, it can finish some deal with task IoV. This layer can accomplish the supportability of administration necessities employing processing and control on-request assets by planning coordinately. As per various requests from IoV, shall separate the coordination model into two classes that are individual coordination model and multitude coordination. The individual model is utilized for tackling the harmonization issues among humans and vehicles and individual article and multitude objects. This model comprises the human (driver) and the driving vehicle. The multitude object comprises all objects of IoV aside from the individual item. Human and vehicle communication understands the tight coupling and finishes the immediate connection through an in-vehicle organization. To settle the bottleneck of correspondence, a clever picture is needed for going about as a specialist for the knowledge of driver and vehicle. The specialist can finish the harmonization of the items through an examination of the individual conduct. The multitude model is utilized for tackling the harmonization issue among humans, vehicles, and climate in IoV from the point of view of collaboration administrations. In this model, humans, vehicles, and climate arrange with one another. The human remembers driver, traveler, and human in climate (rider, person on foot). The vehicle incorporates driving vehicles and leaving vehicles. Similarly, the climate incorporates charging heaps, ecological checking, and data channel administration passageways. Attributable to the nonsymmetric of figuring capacities among human, vehicle, and climate, the all-encompassing detecting of IoV depends on the keen vehicles, yet additionally on the multitude coordination detecting. Humans and vehicles play out a functioning part in the coordination registering through cell phones and vehicles. Notwithstanding, they partake in detachment through wise electronic stations, which is conveyed by ITS. Along these lines, the multitude co-appointment model of IoV comprises humans, vehicles, climate, insightful pictures, and administrations. To adapt to the difficulties of IoV, the knowledge of humans and vehicles should be displayed on the internet. The vehicle and street to fairly see the city traffic information and registered the traffic to acquire the geography of city traffic organization and its attributes, whereupon better IoV administrations can be given. The vehicle cooperation issue to the vehicle speed harmonization issue by figuring if the vehicle direction converges. Vehicles can organize at the crossing point by taking care of the harmonization issue. Ghaffarian et al. changed the traffic issue into a whole number programming issue by examining the two-way single path between segment structures. They tackled the harmonization issue with no significant traffic signals between area climate and diminished the normal deferral adequately. Milan et al. proposed a methodology dependent on V2V and V2I to facilitate processing. In this methodology, driverless vehicles with a few distinctive correspondence guidelines and diverse framework structures can speak with one another, and they settle on choices as per information exchange. For the current exploration, they overwhelmingly center around the vehicle’s harmonization, especially in VANET . Be that as it may, IoV administration additionally requires correspondence assets, calculation assets, and information to arrange in IoV. Besides, there are just a couple of studies that emphasize human–vehicle–climate harmonization.

Closed services are administrations that focus on explicit ventures or stages, especially benefits profoundly associated with the transportation of vehicles. Driving security is one of the overwhelming application records for vehicles and transportation, for instance, dynamic street wellbeing can diminish the likelihood of car crashes and advance transportation wellbeing. In light of shared data about places of vehicles and convergences, speed, and driving vehicle separation, the event of a car crash might be anticipated by V2V and V2I correspondence. Drivers consistently respond rapidly to stay away from auto collisions. The greater part of the examinations on dynamic street wellbeing applications pre predominantly focused on the convergence strife admonishing, surpassing cautioning, crash cautioning, rear-end cautioning, chain impact admonishing, crisis vehicle cautioning, salvage help, crisis brake, petty criminal offense admonishing, traffic state sees, and so on. As of now, the crash admonishing procedures are autonomous program bundles gave by unique gear makers as the premise of frameworks. They give notification of auto collisions, a notice of street conditions (e.g., dangerous asphalt), and rear-end vehicles. To evade a mixture impact, Colombo et al. have shown a technique, which uses the vehicle’s dynamic model to take care of the vehicle booking issues. Most of the functions in ITS are closed service as it is a complex circulated framework joined with cutting-edge innovations in zones of correspondence, detecting, versatile situating, information bases, smart data handling, and programmed control. ITS dominatingly contains six essential subsystems. They are progressed city the board framework, progressed route framework, progressed vehicle control framework, business vehicle the executives, progressed public transportation framework, and progressed metropolitan transportation framework. The insightful traffic the board likewise incorporates ETC, which guarantees vehicles to cross street and extension cost stations at ordinary speed for decreasing the likelihood of blockage. Considering processing assets and capacity assets brought about by huge scope versatile clients, novel metropolitan traffic the executives’ framework is proposed for taking care of the issue of deficient registering and capacity assets dependent on keen transportation cloud [25].

Open administrations in IoV are mostly given by the outsider to clients, which are grouped into on the web and disconnected stream media and human–machine intelligent administrations, including video gathering, climate data, information transmission, web administrations, music downloads, game intelligence, and side of the road administrations. Future portable internet providers are reached out to vehicular administrations, which offer types of assistance for vehicles, for example, Apples “CarPlay.” For the most part, the administrations accommodated clients incorporate two perspectives, specifically customized amusement administrations and transportation administrations. Clients’ amusement benefits dominatingly center around those that can be acquired from the network or different vehicles. For instance, a notice of focal points, nearby online business, and media downloads. In any case, the focal point of customized transportation administrations is prevalently centered around transportation information that the clients ought to recover from networks, for example, way route and HD (high definition) maps for mechanized driving. Telematics additionally includes some open administrations like telematics in taxicabs, which may gather direction information, break down traffic state, and offer opening types of assistance. Telematics is a combination of media transmission and informatics. In addition, it is a helpful framework, which gives data across internet innovation, to be specific vehicular PC frameworks, remote correspondence innovation, satellite route gadgets, trade messages, and voices. Telematics gives capacities about security applications, crisis salvage, guard against burglary, and distant analysis. Telematics can contact with administration focus through remote correspondence to find the flaw precisely, give the shortcoming causes and analysis to look after staff, and guarantee the vehicles travel all the more securely. Using cloud administrations, telematics synchronizes information with other electronic gadgets, gives continuous street condition data, and chooses the best course. Telematics can refresh the most recent guide data to keep up the guide information precise and state-of-the-art. At that point, it can question the data about encompassing offices, stopping plots, shops, and administrations. It can likewise give the elements of phone administrators and one-contact calling focus to diminish activity and encourage clients. All the previously referred administrations center around upgrading the driving well-being and some normal applications. Not many of them join worldwide traffic data and the driver inclination to offer customized assistance, which could turn out to be increasingly more significant in the future. Subsequently, we ought to investigate novel IoV administration.

In IoV, vehicles and foundations access networks utilizing an assortment of remote access advancements. Nonetheless, there exist huge contrasts between various advancements. Subsequently, a transmission control network is needed for protecting these distinctions, which infer that the heterogeneous organizations’ mix is inescapable with the improvement of IoV. To understand the transmission control organization, the heterogeneous organizations must be incorporated with serious level, which will draw in numerous difficulties. Consequently, the mix of heterogeneous organizations has become a hot examination field. SDN can control network traffic deftly through isolating the organization gadget control and information. In SDN, like a pipeline, the network turns out to be wiser, and it can understand the organization’s transmission and control. As indicated by the distinctions created in preparing the vehicular information utilizing diverse correspondence advances (e.g., cell organization and DSRC), a way to deal with shield these distinctions. A novel vehicle correspondence design dependent on SDN. In this engineering, the distinctions of various heterogeneous access advancements could be protected through the SDN trade interface. To dispose of the distinctions of cell organization and broadcast organization, a multi-radio organization joining approach dependent on substance appropriation organization. This combination organization can fulfill ser-indecencies of sound and video. Distributed computing has the upsides of incredible figuring, dynamic booking of the asset, giving on-request benefits, handling huge data productively, and incorporating the executive’s instruments. These favorable circumstances can be utilized for taking care of the issues of data sharing and transmission delay in IoV. Henceforth, joining the cloud and vehicle is an altogether significant improvement of IoV. Vehicloud , which is an engineering dependent on distributed computing, and tackles vehicle correspondence precariousness issues through moving the conventional vehicular organization to support-based design. A novel engineering consolidated vehicle with distributed computing, named V-Cloud , for tackling the correspondence inadequacies issue of V2V and V2I for current 3G/4G. MEC (mobile edge computing) coordinates the Internet and remote organization viably, and it builds the elements of figuring, stockpiling, and information preparing in the remote organization. Also, it assembles an open stage for embedded functions and opens the data communication between remote organizations and administration workers through a remote application interface. MEC coordinates the remote organizations and administrations, and it overhauls the conventional base station to a shrewd base station. For future organization transmission and control, MEC will likewise assume a significant job. Likewise, with the approach of the 5G time, the correspondence postpone will be extraordinarily decreased, and the street data will be instantly sent to the information stage. Thus, the plat structure can control the traffic all the more precisely and actualize V2X correspondence applications [26]. All the previously mentioned advancements don’t consider the vehicle highlight (e.g., vehicle speed and data transmission) for vehicle access and transport, which are needed in IoV and significant for vehicles to associate organizations.

As of now, the organization access innovations of IoV shall be characterized into between vehicle network access advancements and versatile Internet access advances. The entrance advances of bury vehicle networks incorporate DSRC (Dedicated Short Range Communications) and WAVE (Wireless Access in the Vehicular Environment). Also, the portable Internet access innovations incorporate LTE (Long Term Evolution) and WiMAX-WLAN . Vehicles depend on these remote correspondence advancements to get to networks, which can understand the correspondence among vehicles and organizations. DSRC is a kind of effective remote correspondence innovation, which bolsters the moving objective acknowledgment and two-path correspondence with rapid movement in a particular region (generally many meters). DSRC embraces the correspondence standard IEEE 802.11a. DSRC has two working modes: one is to set up the association among vehicles, which is utilized for upgrading the traffic security through being careful separation and cautioning auto collisions. The other is to build up the association among vehicles and streets, which is utilized for facilitating traffic pressure through the ideal course. At present, WAVE innovation has gotten one of the principal access advances to associate with the organization. The WAVE is utilized for taking care of the direct obstructing issue in the actual layer when vehicles access the organization. A multi-need conveyed channel blockage control approach dependent on IEEE 802.11p. The object of this methodology is to guarantee the low crash rate and most extreme transmission likelihood of the high need data [27]. In the investigation of LTE , a methodology of vehicle access network dependent on 4G and LTE-A (LTE–Advanced) [28]. The test outcomes uncover that the methodology can be worked in the vehicle with a speed of 140 km/h. The creators initially summed up the connected examination on LTE research organizations and industry. At that point, they examined the difficulties in the current examination about this issue and anticipated the advancement heading of LTE in IoV [29]. The focus has been given to the foundation of correspondence engineering and model in the LTE-A framework. Additionally, the presentation distinction is somewhere in the range of 2D and 3D channels. Additionally, HUAWEI dispatched LTE-V (LTE–Vehicle) for notice and controlling vehicle impact [30]. In light of the LTE and WLAN, portable Internet can give correspondence among vehicle and vehicle and vehicle and organization. LTE is the third versatile age correspondence standard created by the association venture association. The engineering of LTE is more straightforward, and it can diminish network hubs and complex framework degrees, which lessens the framework delay. Additionally, it decreases the expense of organization sending and support. WiMAX (Worldwide interoperability for Microwave Access) and WLAN (Wireless Local Area Network) are two remote correspondence innovations dependent on IEEE 802.11. Since these kinds of remote access advancements are integral, significant examinations consolidate the two innovations to enable the vehicle to interface with the organization. The chance of joining WiMAX and LTE-A, and analyzed the throughput and deferral of V2I utilizing two innovations. The performance indicated that the innovation can upgrade the correspondence proficiency of V2I utilizing the blend of WiMAX and WLAN . A half-breed of WiMAX and WLAN, named Carlink, can give the principles of vehicle correspondence and security of route frameworks [31].

It is to be seen that each plane collaborates with all the layers in its engineering. For additional insights regarding convention stack functionalities and portrayal, perusers are urged to allude to the comparing articles in [32]. By breaking down these previously mentioned proposed structures in the IoV area, we discovered numerous perspectives that demonstrated that IoV is still in its beginning phase of normalization and shows numerous chances and difficulties for both scholarly world and enterprises specialists, IT engineers, internet suppliers, and so on. This is wonderful particularly while considering the IoV observation from various examinations, regardless of whether it is from modern or scholastic analysts. The thought about perspective used to propose and plan these structures are extraordinary and at times layers are compatible.

  • In Fig. 14.3, the discernment layer functionalities relate to the functionalities introduced in the inserted frameworks and sensors layer in Fig. 14.2. A similar layer is a bit of two layers (2L) (e.g., client cooperation and obtaining) in Fig. 14.4.

  • The coordination layer in Fig. 14.3 is known as a multi-organization edge in Fig. 14.2, while it is known as a correspondence layer in Fig. 14.4.

  • Datacenter/cloud layer in consideration, 2 is parceled along with 3L (artificial understanding layer, application layer, business layer) in Fig. 14.3, while it is disconnected into 2L (Management layer and Business layer) in Fig. 14.4.

Likewise, remark on an issue in the layer’s structure between Figs. 14.3 and 14.4. In Fig. 14.4, there is a preplanning layer, which looks at counterfeit information in Fig. 14.3, going before the correspondence layer. Nevertheless, in Fig. 14.3, the arrangement which occurs in the fake information layer comes after the coordination layer. Another perspective to be examined is the presence of the security submitted layer in Fig. 14.2 which was not present in the 5L-based plans in Fig. 14.3. The correlation may be long while differentiating these models independently, from 3L-based plan to a 13L-based plan.

5 IoV Applications and Resource Management System

Connected vehicles in the system can share a variety of available information to make wise decisions. For example, a cloud-based VANET architecture facilitates the identification of accessible resources in real-time. It can be applicable for cloud-based IoV applications like real-time video sharing, complex computation, dynamic bandwidth sharing, enhanced resource management, and so on. IoV is an emerging technology that integrates multiple sensors, which are placed on roads, vehicles, and devices worn by pedestrians to ensure safe driving and secure vehicle-to-vehicle communication (V2V). Sensors in vehicles collect information such as GPS location, vehicle health conditions, surrounding environment, conditions of the road, and upload the collected data in the cloud. The data will be processed and provide optimized outcomes to the user with the intention of vehicle performance enhancement and safety of drivers, vehicles, and pedestrians [33]. Cloud-based VANET architecture consists of a local VANET cloud network (LVCN), wide VANET cloud network (WVCN), and central VANET cloud network (CVCN). LVCN shares its connected vehicle resources, computational, storage within a mile’s range. Vehicles across LCVN will lose their connectivity from the cloud network. Vehicles inside LCVN can obtain the available mined information such as traffic congestion, traveling time, short routes based on safe route optimization. Each LCVN has dedicated servers attached with other cloud networks in the VANET environment. WVCN has more resources in the cloud network which offers vehicles to be connected and communicated within the WVCN cloud site. WVCN establishes interconnection with sets of LCVN via Wi-Fi, internet, and DSRC. CVCN is like a cellular communication that has a group of WVCN and its servers are connected through the internet. CVCN has a resource-rich cloud network for superfast computations, information transfers which facilitates vehicles to make decisions. Vehicles in CVCN have guided well to face complex issue [34]. Cloud services are offered commercially by several software platforms such as IBM, Google, Oracle, SAP, and so on. The process consists of RT data gathering, transmission, and analysis of data [35]. Cloud-based VANET architecture is described in Fig. 14.8.

Fig. 14.8
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VANET architecture with cloud based

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Cloud-based VANET architecture facilitates fast, reliable, and efficient V2V, V2I, and V2X communication with routing strategy and optimal resource allocation. Thus, it equips rapid implementation of smart cities and capable to manage under cloud-based VANET architecture. The advantages of using a cloud server are capable of fast computing, processing, and analyses in real time. Based on this strategy, some ideal systems were developed under this cloud-based network integrated with IoV, to handle global vehicle management as follows,

  • Smart traffic management

  • Smart accident warning system

  • Privacy and security

  • Smart city design

  • Cost-effective web services

Considering one of the IoV applications, designing a smart city requires certain key technologies which are mentioned in Fig. 14.9. These technologies effectively monitor and control vehicle mobility and improvise the safety and time savings.

Fig. 14.9
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Key technologies for smart city design

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The cloud-based architecture is required to manage all the resources to avoid data collision and provides global communication. It has three stages which are mentioned in Fig. 14.10.

Fig. 14.10
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Resource management in cloud-based architecture

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The design of cloud-based architecture needs to be directed potentially with the following functional parameters which are mentioned in Table 14.1.

Table 14.1 Key design characteristics of resource management system
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RT three-dimensional vehicle tracking : In a cloud-based VANET network, IoV could be applied effectively for traffic management analysis through RT 3Dvehicle tracking. IoV application can provide the 3D map, street, and intersection views with optimal routing strategy to avert traffic obstruction. A vehicle in the network selects the route, will be updated to the driver with RT traffic conditions on the road for the whole trip. This IoV function permits every vehicle in the network, to stock the required route map and can stake their trips with family, friends, and social networks.

IoV has other applications like bandwidth resource sharing (vehicles in the cloud network can stake their bandwidth resources as per their requirements), Enhanced resource management (Intelligent Disaster Management Reinforcement System such as Emergency Medical Services for people affected by the earthquake, flood can be rescued), monitoring, storing, and sharing of trip videos (cloud-based network can store, monitor, and retrieve HD videos in the cloud instead of storing in a large volume of a hard disk). Unique Vehicle Identity (UVI) harmonizes vehicle smart information such as auto insurance, rescue operations, and vehicle remote inspections.

6 Future Directions and Conclusions

With rapid development in internet and communication technologies, traditional vehicles are becoming smart vehicles. IoV has emerged as a global player which interconnects people, vehicles, and things inside the cloud network. The advancements that occurred in areas such as IoT, VANET , and software tools evolved together and bring forth new technology called “IoV.” IoV is a multiplex combined network model which mainly focused on vehicular computing especially cloud computing, intelligent geographic information system, ITS . IoV has major benefits in particular safe driving, traffic administration, active information service, and minimize traffic obstruction. The smart integration of people, vehicles, and things under IoV in addition to focuses safety prospects and also concentrates advanced transport-related services such as autonomous driving and green driving. Communications made in IoV are implemented by Standard development organizations (SDO) like IEEE, 3GPP, and ETSI. This chapter investigates the need for IoV, network paradigms and architectures, resource management, and novel applications. The future direction and prospects of IoV play a huge role shortly by adopting advancements in computing, softwarization technologies, sensoric advancements [36, 37]. Few future IoV implications listed for readers knowledge is as follows:

  • In the future, IoV shall add significant features and adopt advanced technologies, for example, parking slot availability data analytics. SMARTPARK—an algorithm is used for the selection of parking slots, which minimizes the traveling time and maximizes the possibilities to secure a parking spot [38].

  • Image and command hybrid model for autonomous vehicles to detect obstacles using speech recognition or video cameras mounted on the car [39].

  • Data mining technology for driving behavior and safety-relevant applications [40, 41].

  • In smart cities, vehicle tracking and traffic control can be controlled by video camera sensor networks [42].

  • Prediction of vehicle trajectories and future locations can be identified by algorithm-based models [43].

  • Quality of service (QoS) is another future concern which depends on performance metric such as low delay, reliability, centralized control server adjusts routing decisions [44].

  • During the absence of infrastructure support, data exchange, self-configure, and other services can be functionalized by using Fog computing, data distribution of IoV, 5G network functions (expecting 6G to arrive soon), which are the prospects of future IoV [45, 46].

  • Efficient hierarchical clustering protocol (EHCP) for multihop communication in VANETs that offers efficient handling of resources and maintains the multi-local networks in the vehicle movement environment [47,48,49,50].