Vehicular Cloud and Fog Computing Architecture, Applications, Services, and Challenges

Gaba, Priyanka; Raw, Ram Shringar

doi:10.4018/978-1-7998-2570-8.ch014

Cited by 12 publications

(8 citation statements)

References 46 publications

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“…Fog computing for autos is one use for the technology. 132 Another key difficulty in vehicular networks is building an effective multi-hop communication system that can deal with the concealed node issue, high vehicle speeds, lack of infrastructure, and VANET safety application quality of service needs. 123,133 Also, the most difficult task in the VC is providing a system for monitoring and recognizing resources independent of roadside infrastructure.…”

Section: Research Challengesmentioning

confidence: 99%

“…It also saves network capacity. Fog computing for autos is one use for the technology 132 . Another key difficulty in vehicular networks is building an effective multi‐hop communication system that can deal with the concealed node issue, high vehicle speeds, lack of infrastructure, and VANET safety application quality of service needs 123,133 .…”

Section: Research Challengesmentioning

confidence: 99%

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Dependable and reliable cloud‐based architectures for vehicular communications: A systematic literature review

Yang

et al. 2023

Int J Communication

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Traffic congestion, air pollution, fuel wastage, and car accidents are all exacerbated by increased traffic. Thus, vehicular communications, which refer to information transmission between cars, pedestrians, and infrastructures, have lately gained popularity and been extensively explored due to their enormous potential to enable intelligent transportation and various safety applications. Manually piloted cars and automated vehicles can acquire relevant information via vehicular communications to enhance traffic security and boost entertainment services. The basic concept of automobile clouds was originally published in the literature not long ago, and several suggested structural approaches have been presented in this study thus far. Several academics have concentrated on the structural layout to address various problems and, as a result, satisfy user expectations in order to give dependable services. We examined various vehicular cloud topologies in this study. We also offered a complete summary of current network layer research on allowing efficient vehicle communications and examined specific security, architectural, and reliability concerns in vehicular clouds. Also, the taxonomy of vehicular networks was discussed in terms of the service link between vehicular networks and cloud computing. Ultimately, we discussed the research prospects available. The results showed that security and privacy challenges are among the most important challenges.cloud computing, vehicular ad hoc network, vehicular cloud architecture, vehicular communication | INTRODUCTIONBecause of its vast application domains, like commercial-oriented, safety-relevant, and convenience-centered applications, 1-3 vehicular networks have recently gained much study interest. 4 Real-time traffic, notice after a crash, cooperative message transmission, warning of a coordinated collision, and traffic vigilance are some safety-relevant applications that may be categorized. 5 Distant vehicle personalization/diagnostics, digital map downloading, Internet access, value-added commercials and advertisements, and real-time entertainment video relay are included in the commercial-centered application. 6 Route diversions, parking availability, electronic toll collection, and active prediction help are examples of convenience-centered applications. 1,7,8 So, vehicle networks must meet some most stringent standards in all these essential application fields. 2,9 Time-critical Vehicle-to-Vehicle (V2V) safety applications necessitate

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Section: Research Challengesmentioning

confidence: 99%

Section: Research Challengesmentioning

confidence: 99%

Dependable and reliable cloud‐based architectures for vehicular communications: A systematic literature review

Yang

et al. 2023

Int J Communication

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show abstract

“…Data collected by devices, like sensors, wearable devices, embedded devices, mobility prototype, and device usage permit to track a user's behavior, can be obtained and processed it to reveal vital conditions using either machine learning and deep learning-based approaches. Conventional cloud computing-based methods with big data investigation can able to offer reliable service and good performance when dealing decisive IoT-based applications [10,11]. But when a patient needs time and critical medical service requirements, a more robust and higher degree of ease of access is needed.…”

Section: Fog Computingmentioning

confidence: 99%

Challenges and Issues of E-Health Applications in Cloud and Fog Computing Environment

Premkumar

Santhosh

2021

Mobile Computing and Sustainable Informatics

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Smart health care is the recent buzzword in the healthcare environment. Involvement of technology in the healthcare domain provides a platform for remote real-time monitoring and self-management of patients' health. The cloud computing is much utilized for developing technological solutions for an efficient smart healthcare system. Since cloud is a centralized environment, its response time becomes an issue in supporting latency-sensitive obligation in real-time applications. Most solutions in the e-health field depend on immediate decision making over real-time data where latency cannot be tolerated. Fog computing is a distributed infrastructure that overcomes this weakness of cloud computing by having the facility of local storage and processing in providing immediate response for decision making. Hence, thereby, it reduces the network latency and bandwidth usage by decreasing the amount of data sent to the cloud. This combination of fog computing and cloud computing can able to employ a reliable and efficient distributed e-health applications. This paper presents a literature review on the common use of cloud computing and fog computing for providing solutions in health care, along with the challenges that exist in providing solutions through fog computing.

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“…These data are collected and processed using machine learning (ML) or deep learning (DL) techniques to reveal hidden patterns in the data and to track users to diagnose and warn about critical conditions. Cloud-based frameworks, which often employ big data analysis techniques, can achieve reliable and accurate results for general IoT applications that require a rapid response [2], [3], [4]. However, for critical medical IoT-based applications that require higher accuracy, real-time responses, and robust behavior, cloud-based architectures can have a significantly adverse impact in cases of network failure or bandwidth delay, and this may result in medical emergencies or even the loss of life [5].…”

Section: Introductionmentioning

confidence: 99%

Edge Intelligence and Internet of Things in Healthcare: A Survey

2021

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Vehicular Cloud and Fog Computing Architecture, Applications, Services, and Challenges

Cited by 12 publications

References 46 publications

Dependable and reliable cloud‐based architectures for vehicular communications: A systematic literature review

Dependable and reliable cloud‐based architectures for vehicular communications: A systematic literature review

Challenges and Issues of E-Health Applications in Cloud and Fog Computing Environment

Edge Intelligence and Internet of Things in Healthcare: A Survey

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