FogWise: On the limits of the coexistence of heterogeneous applications on Fog computing and Internet of Vehicles

Mendonca, Francisco Ferreira de; Dias, Kelvin Lopes; d’Orey, Pedro M.; Kokkinogenis, Zafeiris

doi:10.1002/ett.4145

Cited by 3 publications

(2 citation statements)

References 44 publications

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“…However, the above studies did not take latency requirements into account. Then, Junior, et al [24] established a request-processing-response-actuation programming model based on distributed auction protocol to match clients and servers and satisfy latency requirements. The simulation results show that VFC can satisfy application requirements under mobility.…”

Section: Related Workmentioning

confidence: 99%

A Reverse Auction Mechanism for Time-Varying Multidimensional Resource Allocation in Vehicular Fog Computing with Cloud and Edge Collaboration

Li¹,

Zhang²,

Sun³

2023

系统科学与信息学报(英文)

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It is a hot issue to allocate resources using auction mechanisms in vehicular fog computing (VFC) with cloud and edge collaboration. However, most current research faces the limitation of only considering single type resource allocation, which cannot satisfy the resource requirements of users. In addition, the resource requirements of users are satisfied with a fixed amount of resources during the usage time, which may result in high cost of users and even cause a waste of resources. In fact, the actual resource requirements of users may change with time. Besides, existing allocation algorithms in the VFC of cloud and edge collaboration cannot be directly applied to time-varying multidimensional resource allocation. Therefore, in order to minimize the cost of users, we propose a reverse auction mechanism for the time-varying multidimensional resource allocation problem (TMRAP) in VFC with cloud and edge collaboration based on VFC parking assistance and transform the resource allocation problem into an integer programming (IP) model. And we also design a heuristic resource allocation algorithm to approximate the solution of the model. We apply a dominant-resource-based strategy for resource allocation to improve resource utilization and obtain the lowest cost of users for resource pricing. Furthermore, we prove that the algorithm satisfies individual rationality and truthfulness, and can minimize the cost of users and improve resource utilization through comparison with other similar methods. Above all, we combine VFC smart parking assistance with reverse auction mechanisms to encourage resource providers to offer resources, so that more vehicle users can obtain services at lower prices and relieve traffic pressure.

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Section: Related Workmentioning

confidence: 99%

A Reverse Auction Mechanism for Time-Varying Multidimensional Resource Allocation in Vehicular Fog Computing with Cloud and Edge Collaboration

Li¹,

Zhang²,

Sun³

2023

系统科学与信息学报(英文)

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“…Peng et al (2020) proposed a double auction mechanism based on multiple features, but they did not take latency requirements into account. Then, Junior et al (2021) established a request-processing-response-actuation programming model based on a distributed auction protocol to match clients and servers and meet latency requirements.…”

Section: Introductionmentioning

confidence: 99%

A combinatorial auction mechanism for time-varying multidimensional resource allocation and pricing in fog computing

Li,

Zhang,

Sun

et al. 2023

International Journal of Applied Mathematics and Computer Scien

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It is a hot topic to investigate resource allocation in fog computing. However, currently resource allocation in fog computing mostly supports only fixed resources, that is, the resource requirements of users are satisfied with a fixed amount of resources during the usage time, which may result in low utility of resource providers and even cause a waste of resources. Therefore, we establish an integer programming model for the time-varying multidimensional resource allocation problem in fog computing to maximize the utility of the fog resource pool. We also design a heuristic algorithm to approximate the solution of the model. We apply a dominant-resource-based strategy for resource allocation to improve resource utilization as well as critical value theory for resource pricing to enhance the utility of the fog resource pool. We also prove that the algorithm satisfies truthful and individual rationality. Finally, we give some numerical examples to demonstrate the performance of the algorithm. Compared with existing studies, our approach can improve resource utilization and maximize the utility of the fog resource pool.

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Fog Computing for Spatial Data Infrastructure: Challenges and Opportunities

Munir¹,

Ali²,

Khiyal

2023

Multi-Disciplinary Applications of Fog Computing

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Fog computing is a promising approach to address the challenges faced by traditional spatial data infrastructure when processing large-scale and real-time data. This chapter examined the opportunities and challenges of using fog computing in SDI through the service dominant logic framework. The study showed that fog computing can improve SDI by providing real-time data processing, improved data security and privacy, and increased accessibility of geospatial data. However, challenges such as data quality and interoperability, collaboration, technical infrastructure, and governance policies need to be addressed. The chapter suggested ways to improve the value co-creation process between fog computing and SDI users, including collaboration and partnership, investment in technical infrastructure, and capacity building initiatives. Future research can investigate the practical implementation and evaluation of fog computing in SDI applications.

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FogWise: On the limits of the coexistence of heterogeneous applications on Fog computing and Internet of Vehicles

Cited by 3 publications

References 44 publications

A Reverse Auction Mechanism for Time-Varying Multidimensional Resource Allocation in Vehicular Fog Computing with Cloud and Edge Collaboration

A Reverse Auction Mechanism for Time-Varying Multidimensional Resource Allocation in Vehicular Fog Computing with Cloud and Edge Collaboration

A combinatorial auction mechanism for time-varying multidimensional resource allocation and pricing in fog computing

Fog Computing for Spatial Data Infrastructure: Challenges and Opportunities

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