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Collaborative Vehicular Edge Computing Towards Greener ITS
DOI:10.1109/ACCESS.2020.2985731.png)
摘要
En 中文
In order to achieve a greener intelligent transport system (ITS), an efficient collaboration between vehicles is required to manage computation task processing with low latency. In this paper, we propose a collaborative edge computing scheme for vehicular Internet-of-things towards a greener ITS. The proposed scheme uses some vehicles as edge nodes, which are responsible for finding task processor nodes on behalf of a task requester node by considering the end-to-end task response time. The proposed scheme employs a two-stage approach where the first stage enables an efficient networking and computing architecture by forming vehicle clusters based on the edge architecture, and the second stage optimizes offloading tasks based on the architecture. We use realistic computer simulations to compare the proposed scheme with existing baselines, and show its superiority in terms of task offloading performance.
Keyword:
Task analysis
Edge computing
Collaboration
Delays
Quality of service
Time factors
Green products
Edge computing
vehicular Internet of Things
green ITS
collaborative intelligence
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期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Deep Reinforcement Learning for Cooperative Content Caching in Vehicular Edge Computing and Networks


