Cloud-Edge Joint Inference Algorithm for Target Recognition in Cloud-Edge Collaborative Intelligence
- DOI
- 10.2991/978-94-6463-108-1_49How to use a DOI?
- Keywords
- cloud-edge computing; joint reasoning; image detection
- Abstract
Cloud-edge co-computing has been widely used for real-time processing of image detection scenarios in IoT. The functional limitations of edge devices and how to effectively determine whether an edge device initiates cloud mode is a new challenge. By proposing a joint inference algorithm. The goal of this algorithm is to automatically determine the trigger conditions for activating cloud mode and improve the effectiveness of cloud-edge collaborative reasoning. The algorithm considers the resource utilization of the edge device, the image recognition accuracy of the edge device, and the network conditions between the edge device and the cloud platform to decide whether to trigger the cloud-edge collaborative inference. Experiments are also conducted on a pathology image recognition project, and the results show that the edge devices show significant improvements in end-to-end reliability and workload reduction.
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Gongyi Xiao AU - Jing Chen AU - Wen Li AU - Hao Sun AU - Chuanfu Zhang AU - Yudong Geng PY - 2022 DA - 2022/12/30 TI - Cloud-Edge Joint Inference Algorithm for Target Recognition in Cloud-Edge Collaborative Intelligence BT - Proceedings of the 2022 International Conference on Computer Science, Information Engineering and Digital Economy (CSIEDE 2022) PB - Atlantis Press SP - 429 EP - 435 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-108-1_49 DO - 10.2991/978-94-6463-108-1_49 ID - Xiao2022 ER -