Ravneet Kaur1,2, Ramkumar Ketti Ramachandran2, Robin Doss1, and Lei Pan1
1 School of Information Technology, Deakin University, Victoria, Geelong, Australia
2 Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, Rapura, India
The term “vehicular communication” was first coined in 1999 by Klaus Eitzenberger to attain safety, traffic control, dynamic navigation aids, and the mobile office. This invention was related to the centralized approach where computers were performing network applications, transmission, reception, recording, or processing data between vehicles, according to Sun et al. [1]. Later on, the concept of distributed message communication came into existence. According to Briesemeister and Hommel [2], radio communications effectively enable the distributed message dissemination strategy in vehicles. However, Xu et al. [3] studied the feasibility for vehicle safety messages in dedicated short range communication (DSRC) and analyzed the memory‐less channel modeling. IEEE 802.11p with DSRC followed a WAVE architecture for communication between roadside unit (RSU) and on‐board unit (OBU). The WAVE (wireless access in vehicle environment) architecture uses 27 Mbps of data rate with a 5.9 GHz frequency range. The IEEE 802.11p standard plays a vital role in vehicular ad hoc networks (VANETs).
Considering the safety applications, the focus of the automobile industry has been diverted to electronic technologies. The car industry has installed collision detection sensors and electronic control units (ECUs) for making transportation intelligent. Besides, the research community has provided various solutions for addressing road fatalities, communication range, message delivery, rapid topology change, and mobility pattern. Other issues such as channel modeling, bandwidth wastage, and repetitive message broadcasting to the nodes are prominent. Thus, a suitable emergency message dissemination strategy is applied to the healthcare services, police, and other related infrastructure for immediate help.
This chapter discusses emergency message dissemination in vehicular environments. We consider the multi‐domain perspective of the emergency message dissemination regarding the reactive response toward a road fatality in various traffic scenarios. This emergency notification is flagged to the nearby hospitals, pharmacies, and other infrastructure in the VANET. We chose to focus on the role of VANETs with Internet of Things (IoT), fog computing, and blockchain for the healthcare system. Thus, most recent technologies and future trends represent state‐of‐the‐art solutions and build the framework for vehicular communications to deal with emergencies.
The chapter is organized as follows:
In VANETs, vehicles are treated as mobile nodes and are equipped with OBUs and ECUs. These resources are useful for disseminating messages during emergencies. In principle, there are three VANET dissemination strategies, namely (i) pull, (ii) push, and (iii) hybrid. The “push down” strategy is favorable for safety applications in VANETs, while the built‐in units in the vehicles monitor environmental conditions and disseminate messages. For the successful and appropriate traversing of the message, traveling path, traveling time, and traveling mode are the crucial factors. With the increase in traffic, road congestion is another issue. To solve these traffic‐related issues and saving human lives, Varun Chand and Karthikeyan [4] listed several available technologies. Figure 9.1 presents the applications of the multi‐domain behavior of VANETs.
The following subsection describes various technologies in trend with VANETs.
Internet of Things (IoT) is a computing concept that connects the devices embedded with electronics, sensors, and actuators. It builds the network by enabling physical devices such as vehicles and homes to exchange data. Three networks are formed when IoT is combined with vehicles—inter‐vehicle network, intra‐vehicle network, and vehicular mobile Internet. These three network types support various applications, including smart cities, environment management, energy management, medical healthcare system, building automation, transportation, and social networking [4].
The limitation of IoT is the storage of electronic devices. To fulfill the emergency message dissemination requirement, vehicles require other technologies. A solution to process data is sending data through the cloud but this presents issues such as lack of mobility support and high‐end to end delay. Hence, fog computing has been proposed to overcome these shortcomings [5].
Fog computing with VANETs is a promising approach to overcome the delay in a decentralized network and optimize the bandwidth usage, thus named vehicular fog computing. Fog computing provides decentralization to all the nodes and reduces overhead on the core network layer. These nodes are distributed geographically and hence create a layer, names fog computing layer. While communicating with the fog computing layer, vehicles act as fog computing nodes and fog computing users according to the service required. When the vehicles are parked or in traffic jams, they act as fog computing nodes and have minimum storage capacity due to flooding of message communication however, posses high efficiency and low latency [5].
This approach leads to offload the RSUs tasks, autonomous driving, video crowdsourcing, content distribution, smart traffic light, and decision support system [6]. For example, during the event‐driven applications, the RSU contributes by investigating the free parking slot for the emergency vehicle. Similarly, a smart traffic light system plays a vital role by sensing the autonomous vehicle driving toward hospitals and thus supports the healthcare system.
The major drawback of fog computing with VANETs is a high end‐to‐end delay, high bandwidth usage, weak security, and poor reliability. More research is needed in this domain for applications that are more time sensitive. Though this approach is useful for quickly saving the patient records, it should be done securely.
Blockchain with VANETs is the emerging research area that provides a secure, authenticated, and trusted environment for V2X (vehicle‐to‐everything) communication. It is pertinent to facilitate recording and tracking resources with a centralized computing platform. Blockchain maintains a ledger for event message exchange to avoid collateral damage. There are various advantages of using blockchain with VANETs such as secure data, location privacy to control traffic congestion due to fake messages, non‐repudiation, transparency, and electronic payment scheme [7]. While communicating messages from one vehicle to another or to infrastructure, the data message is divided into block segments. Once the block is added to the chain, the data block cannot be modified. For any update or modification in the block, smart contracts will be used.
Blockchain with VANETs has slow data storage, long overhead, and long verification time, which affect the system’s performance, increase deployment cost, and limit scalability [8].
Table 9.1 lists the limitations of VANETs with IoT, Fog Computing, and Blockchain.
Table 9.1 Limitations of VANETs with (a) IoT being an IoV, (b) fog computing being a vehicular fog computing network, and (c) blockchain.
IoT | Fog computing | Blockchain |
---|---|---|
low storage capacity | more end‐to‐end delay | low capacity |
security | high bandwidth usage | increased overhead |
technology over‐reliance | security | increased verification time |
reliability | high deployment cost |
The increased number of deaths due to overcrowded roads and traffic mismanagement opens various research and development opportunities in VANETs. The development in e‐health services and smart mobility ease the elder person checkups. The deployment of wireless e‐health services and on‐time delivery of reliable medication prompts the healthcare stakeholders. The growing demand of VANETs within healthcare provides various benefits and open challenges to the community that is significantly different from the random topology change or mobility patterns of VANETs [9].
Another advancement in VANETs within healthcare is telemedicine to develop smart healthcare systems in rural and urban areas. This mobile solution supports developing countries such as India, where building the physical structures is quite tricky. This consultation is more feasible and cost effective as it reduces medical costs, travel expenses, and time. Such solutions are especially useful during pandemics and for the people who live in rural areas [10].
As shown in Figure 9.2, during emergency message dissemination, any technology in IoT, fog computing, and blockchain can provide useful information to the appropriate infrastructure. However, the clustering framework improves communication by providing the opportunity for full connectivity and maximum coverage. The responsibility of data packet sharing is distributed to all other nodes and thus balances the load. This setup facilitates fast communication. The collaboration of connected vehicles helps implement real‐time applications. In particular, several routing protocols and frameworks are presented in Kaur et al. [11].
In Section 9.3.1, a case study is presented to show how the emergency message dissemination notification is effective in a real‐time environment.
When a serious traffic accident happens, the time taken by the emergency services to arrive is crucial. Most deaths during accidents happen due to the unavailability of emergency services. According to the World Health Organization (WHO), by 2030, road fatalities will be the seventh leading cause of death worldwide. To reduce road accidents, the knowledge of the road events such as congested roads, notification of road fatality, or other emergencies plays a crucial role. For example, the notification of road accidents will notify the associated personals such as hospitals, pharmacies, and the police so as to reduce the delay in providing emergency aid.
Perhaps that will be the automobile industry’s future, where vehicles talk to one another and with the infrastructure. Currently, the US Department of Transportation (DoT) is working on connected vehicles. Even that would greatly impact this pandemic where in developing countries such as India, people need E‐permits to enter another state.
VANETs provide an opportunity to cover large areas using clustering, in which the cluster head (CH) is selected to pass the emergency message to all the vehicles timely, as shown in Figure 9.2. They will help control the traffic flow and reduce the resulting congestion at accident sites. This arrangement will drastically reduce road fatalities, save human lives, reduce fuel consumption, and save drivers’ money, ultimately making our transportation safer and smarter.
Different techniques can be used to quickly disseminate emergency messages to support the healthcare system. Section 9.4 elaborates on various technologies.
Launching an intelligent transportation system (ITS) is a way to provide managed and controlled traffic on the road. This will make use of smart, safe, and synchronized ways of transportation. There is a tremendous increase in the number of vehicles that leads to traffic congestion and traffic accidents. During such emergencies, there is a need to communicate the event information to the nearby vehicles, hospitals, pharmacies, police, and many more. There is a possibility that all vehicles would not receive the emergency information due to their rapid topology change or they would not lie in the communication range. Thus, there is a need to ensure the full connectivity of the network and reliable communication. It helps secure the data from intruders, spoofing, denial of service, and many more attacks. According to Kaur et al. [11], clustering is the solution for such problems. Clustering plays an instrumental role in providing the maximum coverage by selecting the most relevant CH selection parameters. When integrated with various technologies in ITS, this framework will act as a support for the healthcare system.
The following subsections describe recent technologies to facilitate emergency situations.
When vehicles are moving on the road, the CH is selected as the group head. The group members and their neighboring nodes’ positions can be identified by the hardware components and system controller modules. By knowing the position ID, location ID, and other parameters, a realistic setup can be established to optimize the road traffic.
Whenever there is a road accident, to avoid traffic jams, congestion on the road, and facilitate immediate first aid, a structure is needed to broadcast all the information in the vicinity. Communicating such sensitive information is a crucial task because there are chances of spoofing. Hence, an attacker may change the information. Another issue is the link breakage due to rapid topology change. The mobile nature of VANETs has different patterns of movement. Thus, there is a need for a full‐connectivity structure to disseminate emergency messages. One of the most prominent solutions is clustering [11]. Using the appropriate framework for delivering messages to the RSUs and other infrastructure, vehicles can communicate within the specified range. If the vehicles are out of range, clustering is the solution. In clustering, CH selection is based on metric selection. The selection of metrics is application‐specific. If there is an emergency event, then time is the most important parameter. If there is retrieving of patients’ data, then clustering with privacy preservation is the suitable approach.
Another critical parameter is the traffic scenario. The selection of parameters also depends on the sparse and dense traffic scenario. If there are less vehicles and are far from each other, link breakage is the problem. If jammed vehicles caused traffic congestion, bandwidth wastage and increased overhead become the challenge. Thus, various optimized clustering techniques are provided to deal with the real challenges of VANETs. However, very little work has been done on the role of clustering in VANETs with healthcare. There is a wide scope of the role of clustering in the healthcare system. Other advantages of the clustering in VANETs with healthcare are listed below.
However, network congestion often occurs in high‐density areas associated with issues such as flooding, broadcast storm, channel modeling, and security.
The development of IoT with VANETs enhances the commercial interest in healthcare management. The Internet of Vehicle (IoV) [12] is helpful in monitoring the health of patients and maintaining the records. Various architectures and communication protocols have been proposed to update the status of patients regularly. This type of solution acts as a possibility of rescue for the patients during emergencies. Another possible use case is road fatalities. If the communication quickly reaches the nearby hospital or broadcasted within the vicinity,, the injured could have been saved. The following are the advantages of IoV.
Besides, there are various limitations such as bandwidth wastage, link breakage, intruder attack, connectivity issues, coverage area, unreliable network connectivity, resource utilization, and broadcast storm. Thus, clustering plays a vital role in IoV. From the above discussion, it can be concluded that there are various applications in IoV that need to be explored. Working with sensors and collecting information from the environment help predict the real‐time expenses of deploying the VANET systems during transportation to reduce the waste and increase efficiency [13].
Nowadays, much interest has been driven to the VANETs and fog computing. According to Popescu et al. [14], various fog Computing architectures are proposed. Fog computing nodes act as RSUs and are responsible for group formation to ensure message dissemination to the complete network and provide secure route services. RSUs can be deployed on the fog computing nodes, and data processing is the extended feature. Fog computing nodes’ distributed control at different geographic locations is responsible for mobile communication, whereas the centralized control is for static communication. Having the group head as a fog computing node in a small area acts as a small hub of reports and online treatment directory for patients [14]. All the records with comparison metrics could be available to the healthcare workers to treat the patients. Thus, fog computing nodes will act as a repository while the patient is in an emergency. The following are the advantages of fog computing:
However, various issues exist in vehicular fog computing, including unpredictable trajectory, scalability, mobility of vehicles, frequent interruptions, link breakage, malicious vehicle joining, network flooded by irrelevant data, chances of data modification, reliability, and security of the network [15].
Various secure protocols have been proposed considering the trust factor. During the retrieval of distributed data from different geographic locations, locations act as unique clusters. The data can be traversed through blocks at the time of emergency. Thus, sensitive data is shared in the hospital vicinity. These records are distributed in various hospitals defined under a unique ID to retrieve the previous consultation. These records are generally called electronic medical records (EMR). For accessing these records in a secure manner, blockchain plays a crucial role [16].
With numerous applications in blockchain with VANETs, the technical implementation lacks a data‐sharing and ‐management system and thus is unable to maintain traceability [7]. When data flow happens during an emergency, there is a need for storage space. This will increase the bloating problem. The rapid topology change and mobility of nodes make proof‐of‐work (PoW) difficult by having a limited time for exchanging information blocks. This information exchange depends on the trust factor. Once the nodes are verified, the information exchange happens. The mobile nature of nodes cannot provide an accurate analysis of nodes that can participate in block propagation.
Various solutions are provided in Kim [17] such as security and credibility, real identity versus public keys, smart contracts with VANETs, and energy contributions. However, the impact of mobility on nodes and its metrics are not addressed for blockchain performance. Nevertheless, blockchain does not fully support VANETs. Thus, other challenges include the addition of blocks and exchange of blocks in mobile nodes of a blockchain system. The following are the various advantages where blockchain is used in VANETs [18]:
In this chapter, we have discussed various technologies, including IoT, Fog Computing, and Blockchain with respect to VANETs and the role of emergency message dissemination using those technologies in the healthcare system. However, we concluded that a particular combined structure needs to be proposed for benefiting the healthcare community and the public. Figure 9.3 shows the diagrammatic representation of the multi‐domain future perspective of VANETs. This figure explains the two following aspects:
From the above discussion, it can be concluded that various research domains are open for research.
VANET is the most promising research area and offers various safety applications. Because of vehicles’ unpredictable movement and rapid topology change, the automobile industry is working in the direction of smart transportation. In 2006, the US DoT had identified eight warning notifications in which vehicles were communicating with roadside equipment (RSE). To evaluate the proposed work and predict the VANET system’s performance, it is costly to establish a new setup or work in a real‐time environment. Thus, network simulators, traffic simulators, and testbeds are used to analyze the proposed work before market launch [19]. The following is the discussion on this testing content.
Upcoming ITS integrated with multi‐domain technologies will offer a revolution toward global automation, the response to emergency situations, and human safety. Different techniques have been explored in this chapter. The IEEE, Florida DoT, and National Highway Traffic Safety Administration (NHTSA) which is part of the US DoT are the leading bodies for providing funds for innovations in ITS. As shown in Figure 9.4, various research challenges are identified to support VANETs with the healthcare system. These research directions need further research and investigation. The open research areas are listed below.
International workshops, summits, industrial events, testbeds, and conferences are provided for delivering transportation solutions. We have divided this discussion into four aspects: (i) industrial events, (ii) testbeds, (iii) conferences, and (iv) summits.
Considering the research community, in continuation with international workshops on OMNET++, the 7th OMNET++ Community Summit was organized in 2020. This summit provided lively discussions, keynotes, tutorials, and ongoing demonstrations to the researchers and helped them to sort various implementation‐related issues that occurred during their research. The focus is to bring all the OMNET++ developers and tools together with novel ideas in network simulators.
In this chapter, we provide the role of VANETs in healthcare from a multi‐domain perspective. The effectiveness and need of IoT, fog computing, and blockchain with VANETs give the upcoming researchers a new direction. Overseeing the traditional VANET structure, we observe the emerging trend and the broad scope of VANETs in healthcare systems. Beyond various safety and non‐safety applications in VANETs, we present a case study and its implications in multiple crucial factors, including full connectivity, maximum coverage area, and scalability. We argue that clustering is a promising approach for achieving excellent results for emergency message dissemination. The future trends include readings, summits, workshops, and conferences in VANETs.
Ravneet Kaur is a student of higher degree by research at Deakin University, Geelong, Australia, with the Research Partner Department of Computer Science and Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India, under Deakin India Research Initiative (DIRI) programme.
Dr. K.R. Ramkumar is PhD in computer science and engineering from Anna University, Chennai, India, having 17 years of teaching and research experience. He is currently working as an associate professor, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India. His areas of expertise are network security, key management, and relational database management systems in advancement. His research includes solving the routing issues, dealing with security and node failure apprehensions of wireless sensor networks. Much of his work has been on improving the understanding, design and performance analysis of different routing and security algorithms of Wireless Sensor Networks (WSN). He is also working with the Extensible Markup Language (XML) and resolving the data integrity and consistency issues on web communications.
Prof. Robin Doss is a professor of information technology and the Deputy Head of the School of Information Technology. Robin leads the Internet of Things (IoT) and Cyber Physical Systems (CPS) security program at the Deakin Centre for Cyber Security Research and Innovation (CSRI) and is the Co‐Director of the IoT research cluster at Deakin. He is a senior member of the IEEE.
Dr. Lei Pan received his PhD in computer forensics from Deakin University, Australia, in 2008. He is currently a senior lecturer with the School of Information Technology, Deakin University. His research interests are cyber security and IoT. He has authored 50+ research papers in refereed international journals and conferences.