Context-Aware Object Detection for Vehicular Networks Based on Edge-Cloud Cooperation
Author | Guo, Jie |
Author | Song, Bin |
Author | Chen, Siqi |
Author | Yu, Fei Richard |
Author | Du, Xiaojiang |
Author | Guizani, Mohsen |
Available date | 2022-11-29T10:54:23Z |
Publication Date | 2020-07-01 |
Publication Name | IEEE Internet of Things Journal |
Identifier | http://dx.doi.org/10.1109/JIOT.2019.2949633 |
Citation | Guo, J., Song, B., Chen, S., Yu, F. R., Du, X., & Guizani, M. (2019). Context-aware object detection for vehicular networks based on edge-cloud cooperation. IEEE Internet of Things Journal, 7(7), 5783-5791. |
Abstract | Due to high mobility and high dynamic environments, object detection for vehicular networks is one of the most challenging tasks. However, the development of integration techniques, such as software-defined networking (SDN) and network function visualization (NFV), in networking, caching, and computing provides us with new approaches. In this article, we propose a novel context-aware object detection method based on edge-cloud cooperation. Specifically, an object detection model based on deep learning is established in the cloud server. Different from other methods, to further explore the underlying inner spatial features of collected images, the visual objects of images are regarded as nodes and the spatial relations between objects as edges, then a type of message-passing method is employed to update the nodes' features. In the mobile edge computing (MEC) servers, the context information and captured images of the vehicular environments are extracted and then are used to adjust the object detection model from the cloud server. In this way, the cloud server cooperates with the MEC servers to realize context-aware object detection, which improves the adaptation and performance of the detection model under different scenarios. The simulation results also demonstrate that the proposed method is more accurate and faster than the previous methods. |
Sponsor | This work was supported in part by the National Natural Science Foundation of China under Grant 61772387 and Grant 61802296, in part by the Fundamental Research Funds for the Central Universities under Grant JB180101, in part by the China Post-Doctoral Science Foundation under Grant 2017M620438, in part by the Fundamental Research Funds of Ministry of Education and China Mobile under Grant MCM20170202, in part by the National Natural Science Foundation of Shaanxi Province under Grant 2019ZDLGY03-03 and Grant 2019JQ-375, and in part by the ISN State Key Laboratory. |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | Context-aware edge-cloud cooperation object detection vehicular networks |
Type | Article |
Pagination | 5783-5791 |
Issue Number | 7 |
Volume Number | 7 |
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