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Resource Management approaches to Internet of Vehicles

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Abstract

The Internet of Vehicles (IoV) has become a significant issue in designing smart cities. Many applications and services are provided in IoV for various purposes. They need the resources for the computation and data collection. One of the open issues in IoV is resource management because of resource limitation, resource heterogeneity, and dynamic networks. To our knowledge, no systematic and thorough research in resource management methodologies was conducted in IoV, despite the critical nature of resource management challenges. This paper analyzes the recently published studies on resource management in IoV. Our analysis shows that resource allocation has the most utilization rate of resource management approaches at 30%. The most critical parameter in resource allocation is cost, which includes energy, time, price, and processing capacity. The analytical reports show those cost parameters have the most evaluation in the approaches by 19%. Furthermore, we propose a taxonomy for resource management in IoV and extract challenges and open issues in this field. It can be a start point to suggest new methods for resource management in IoV.

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Authors and Affiliations

  1. Pattern Recognition and Machine Learning Lab, Gachon University, 1342 Seongnamdaero, Sujeonggu, Seongnam, 13120, Republic of Korea

    Mehdi Hosseinzadeh

  2. Computer Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Shirin Abbasi

  3. Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan

    Amir Masoud Rahmani

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  1. Mehdi Hosseinzadeh
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  2. Shirin Abbasi
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Correspondence to Amir Masoud Rahmani.

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Hosseinzadeh, M., Abbasi, S. & Rahmani, A.M. Resource Management approaches to Internet of Vehicles. Multimed Tools Appl 82, 46811–46844 (2023). https://doi.org/10.1007/s11042-023-15590-9

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