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Dependence-Aware Edge Intelligent Function Offloading for 6G-Based IoV

delete2022-01-01
delete16
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OA
AI
董
董洛兵 (Luobing Dong) *
H
Honghao Gao *
W
Weili Wu
Q
Qiwen Gong
Y
Yanfei Liu
DOI:10.1109/TITS.2022.3148229delete
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Abstract

Abstract

En 中文
Using the increasingly wireless communication capacity of 5G/6G technology, edge intelligence (EI) enables modern vehicles to leverage the powerful computing resources of edge servers scattered aside the roads to implement intelligent transportation applications (ITA). The running of these intelligent applications is always accompanied by the calculating and transmitting of massive amounts of road situation data. For the protection of drivers and passengers, these complex processes should be handled in an ultra-reliable and low latent manner. Intelligent processing function offloading from terminals to edge servers is a promising approach to address these issues. However, the runtime environment specification of each intelligent processing function and the interdependence between two consecutive functions pose a challenge for the assignment of the offloaded functions among edge servers. In this paper, we propose a dependence-aware edge intelligent function offloading scheme for 6G-based Internet of Vehicle (IoV). All traditional ITAs are split into different chains of standard intelligent functions. Each edge server can provide some specific intelligent functional services. These services can receive data from cars and serve as different intelligent functions. Then, an intelligent application offloading scheme is changed into an embedding scheme of a service chain. An NP-hard objective function is constructed using a multi-winner committee selection model for this offloading service chain embedding problem. We design two algorithms to get the optimal assignment of intelligent functions using a greedy strategy and dynamic programming strategy separately. Finally, experiments show that when the proportion of vehicles meeting the constraint conditions is not in [9%,10%], our algorithms are fast.
Keywords:
Face recognition
Heuristic algorithms
Servers
Computer architecture
Automobiles
Edge computing
5G mobile communication
IoV
edge intelligence
multi-winner committee selection
dynamic programming
offloading

Journal

IEEE Transactions on Intelligent Transportation Systems cover
IEEE Transactions on Intelligent Transportation Systems
IF:
8.4
Papers:
9.7K
Citations:
6.3W

Organization

U
University of Texas Dallas
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Papers: 5.0K
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U
university of texas system
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X
Xidian University
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Papers: 1.9W
Citations: 9.7K
S
shanghai university
Scholars:
3.9W
Papers: 2.7W
Citations: 52
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