An Incentive Mechanism for Computing Resource Allocation in Vehicular Fog Computing Environment

Nazih, Ossama; Benamar, Nabil; Addaim, Adnane

doi:10.1109/3ict51146.2020.9312007

Cited by 12 publications

(2 citation statements)

References 12 publications

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“…By lever-aging parked vehicles for connectivity and computation clusters and utilizing moving vehicles for dynamic communication scenarios, VFC addresses challenges unique to vehicular environments, ushering in a paradigm that enhances vehicular communication and computation capabilities at the network's edge [24]. Several VFC assumptions have been proposed in the literature, including vehicular cloudlets (cloudlets transported by moving vehicles) [25]- [29]. Hou et al [30] provided an example of cloudlet deployment.…”

Section: From Fog Computing To Vfcmentioning

confidence: 99%

Toward Secure and Trustworthy Vehicular Fog Computing: A Survey

Nazih,

Benamar,

Lamaazi

et al. 2024

IEEE Access

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The integration of fog computing in vehicular networks has led to significant advancements in road safety, traffic control, entertainment, and comfort services. Vehicular Fog Computing (VFC) emerges as an optimistic solution, offering a pathway to responsive service requests. VFC uses either onboard vehicle computers or vehicles as fog infrastructure between the underlying networks and the cloud, addressing the limitations of centralized data processing in traditional cloud computing. However, VFC faces security vulnerabilities due to the open nature of its deployment. In this survey, we explore the security threats confronting VFC and review existing solutions related to their detection and mitigation capabilities. This paper provides a comprehensive overview of the foundational concept of Fog Computing, VFC architectures, and their critical role in various intelligent computing applications. Moreover, it spotlights the trust and security concerns in deploying VFC and real-time big data analytics within the vehicular environment. This survey identifies pressing issues and outlines potential research directions, offering insights for the research community to address while designing secure VFC architectures.

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Section: From Fog Computing To Vfcmentioning

confidence: 99%

Toward Secure and Trustworthy Vehicular Fog Computing: A Survey

Nazih,

Benamar,

Lamaazi

et al. 2024

IEEE Access

Self Cite

View full text Add to dashboard Cite

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“…Luo et al, 118 proposed an incentive‐aware micro computing cluster formation problem as a coalition game. Similarly, Nazih et al, 119 proposed a Stackelberg game‐based incentive mechanism for vehicular fog networks. Incentive models were also proposed in similar domains such as in D2D offloading 120 .…”

Section: Fog Computing Challenges and Solutionsmentioning

confidence: 99%

A decade of research in fog computing: Relevance, challenges, and future directions

Srirama

2023

Softw Pract Exp

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Recent developments in the Internet of Things (IoT) and real‐time applications, have led to the unprecedented growth in the connected devices and their generated data. Traditionally, this sensor data is transferred and processed at the cloud, and the control signals are sent back to the relevant actuators, as part of the IoT applications. This cloud‐centric IoT model, resulted in increased latencies and network load, and compromised privacy. To address these problems, Fog Computing was coined by Cisco in 2012, a decade ago, which utilizes proximal computational resources for processing the sensor data. Ever since its proposal, fog computing has attracted significant attention and the research fraternity focused at addressing different challenges such as fog frameworks, simulators, resource management, placement strategies, quality of service aspects, fog economics and so forth. However, after a decade of research, we still do not see large‐scale deployments of public/private fog networks, which can be utilized in realizing interesting IoT applications. In the literature, we only see pilot case studies and small‐scale testbeds, and utilization of simulators for demonstrating scale of the specified models addressing the respective technical challenges. There are several reasons for this, and most importantly, fog computing did not present a clear business case for the companies and participating individuals yet. This article summarizes the technical, non‐functional, and economic challenges, which have been posing hurdles in adopting fog computing, by consolidating them across different clusters. The article also summarizes the relevant academic and industrial contributions in addressing these challenges and provides future research directions in realizing real‐time fog computing applications, also considering the emerging trends such as federated learning and quantum computing.

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A Security and Privacy-Preserving Accessing Data Protocol in Vehicular Crowdsensing Using Blockchain

Alamer

Basudan

2022

Proceedings of Seventh International Congress on Information and Communication Technology

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An Incentive Mechanism for Computing Resource Allocation in Vehicular Fog Computing Environment

Cited by 12 publications

References 12 publications

Toward Secure and Trustworthy Vehicular Fog Computing: A Survey

Toward Secure and Trustworthy Vehicular Fog Computing: A Survey

A decade of research in fog computing: Relevance, challenges, and future directions

A Security and Privacy-Preserving Accessing Data Protocol in Vehicular Crowdsensing Using Blockchain

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