An Integrated Cloud-Edge-Device Adaptive Deep Learning Service for Cross-Platform Web

Yakun Huang, Xiuquan Qiao, Jian Tang, Pei Ren, Ling Liu, Calton Pu, Junliang Chen

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Deep learning shows great promise in providing more intelligence to the cross-platform web. However, insufficient infrastructure, heavy models, and intensive computation limit the use of deep learning with low-performing web browsers. We propose DeepAdapter, an integrated cloud-edge-device framework that ties the edge, the remote cloud, with the device by cross-platform web technology for adaptive deep learning services towards lower latency, lower mobile energy, and higher system throughput. DeepAdapter consists of context-aware pruning, service updating, and online scheduling. First, the offline pruning module provides a context-aware pruning algorithm that incorporates the latency, the network condition, and the device's computing capability to fit various contexts. Second, the service updating module optimizes branch model cache on the edge for massive mobile users and updates the new model pruning requirements. Third, the online scheduling module matches optimal branch models for mobile users. Also, a two-stage DRL-based online scheduling method named DeepScheduler can handle high concurrent requests between edge centers and remote cloud by designing the reward prediction model. Extensive experiments show that DeepAdapter can decrease average latency by 1.33x, reduce average mobile energy by 1.4x, and improve system throughput by 2.1x with considerable accuracy.

Original languageEnglish (US)
Pages (from-to)1950-1967
Number of pages18
JournalIEEE Transactions on Mobile Computing
Volume22
Issue number4
DOIs
StatePublished - Apr 1 2023
Externally publishedYes

Keywords

  • DNN compression
  • Mobile computing
  • adaptive service
  • cross-platform web
  • edge computing

ASJC Scopus subject areas

  • Software
  • Electrical and Electronic Engineering
  • Computer Networks and Communications

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