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Cited by 25IoT and Edge/Fog ComputingVehicular Ad Hoc Networks (VANETs)Energy Efficiency in Computing

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A survey on computation resource allocation in IoT enabled vehicular edge computing

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Naren, Gaurav, Abhishek Kumar, Sahu, Nishad, Dash, Abhinash Prasad, Chalapathi, G. S. S., Chamola, Vinay·2022·Complex & Intelligent Systems
DOI 10.1007/s40747-021-00483-x
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Abstract

The number of vehicles is increasing at a very high rate throughout the globe. It reached 1 billion in 2010, in 2020 it was around 1.5 billion and experts say this could reach up to 2–2.5 billion by 2050. A large part of these vehicles will be electrically driven and connected to a vehicular network. Rapid advancements in vehicular technology and communications have led to the evolution of vehicular edge computing (VEC). Computation resource allocation is a vehicular network’s primary operations as vehicles have limited onboard computation. Different resource allocation schemes in VEC operate in different environments such as cloud computing, artificial intelligence, blockchain, software defined networks and require specific network performance characteristics for their operations to achieve maximum efficiency. At present, researchers have proposed numerous computation resource allocation schemes which optimize parameters such as power consumption, network stability, quality of service (QoS), etc. These schemes are based on widely used optimization and mathematical models such as the Markov process, Shannon’s law, etc. So, there is a need to present an organized overview of these schemes to help in the future research of the same. In this paper, we classify state-of-the-art computation resource allocation schemes based on three criteria: (1) Their optimization goal, (2) Mathematical models/algorithms used, and (3) Major technologies involved. We also identify and discuss current issues in computation resource allocation in VEC and mention the future research directions.

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Metadata

Authors
Naren, Gaurav, A. K., Sahu, N., Dash, A. P., Chalapathi, G. S. S., & Chamola, V.
Affiliations
Birla Institute of Technology and Science, Pilani (IN)
Corresponding author
  • Gaurav, Abhishek Kumar
  • Sahu, Nishad
  • Dash, Abhinash Prasad
  • Chalapathi, G. S. S.
  • Chamola, Vinay
ORCID
Venue
Complex & Intelligent Systems
Publisher
Springer Science and Business Media LLC
Published
2021-07-31
Volume
8
Issue
5
Pages
3683-3705
ISSN
  • 2198-6053 (ISSN-L)
  • 2199-4536
DOI
10.1007/s40747-021-00483-x
OpenAlex
W3188253987
Cited by
25
References
2
Citations by year
2026: 4 · 2025: 8 · 2024: 8 · 2023: 3 · 2022: 2
FWCI
1.46
Type
journal article
Language
en
Open access
Licence
Locations
Complex & Intelligent Systems (publishedVersion, cc-by)
Funders
  • Department of Science and Technology, Ministry of Science and Technology, India
  • Science and Engineering Research Board (ECR/2018/001479)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
  • Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
Keywords
computing resource allocation, vehicular edge computing, Internet of Things, vehicular networks, power consumption, quality of service, network stability, optimization model, software-defined networking, blockchain, artificial intelligence

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