Lightweight convolution neural networks for mobile edge computing in transportation cyber physical systems

Junhao Zhou, Hong Ning Dai, Hao Wang

Research output: Contribution to journalJournal articlepeer-review

24 Citations (Scopus)


Cloud computing extends Transportation Cyber-Physical Systems (T-CPS) with provision of enhanced computing and storage capability via offloading computing tasks to remote cloud servers. However, cloud computing cannot fulfill the requirements such as low latency and context awareness in T-CPS. The appearance of Mobile Edge Computing (MEC) can overcome the limitations of cloud computing via offloading the computing tasks at edge servers in approximation to users, consequently reducing the latency and improving the context awareness. Although MEC has the potential in improving T-CPS, it is incapable of processing computational-intensive tasks such as deep learning algorithms due to the intrinsic storage and computingcapability constraints. Therefore, we design and develop a lightweight deep learning model to support MEC applications in T-CPS. In particular, we put forth a stacked convolutional neural network (CNN) consisting of factorization convolutional layers alternating with compression layers (namely, lightweight CNN-FC). Extensive experimental results show that our proposed lightweight CNN-FC can greatly decrease the number of unnecessary parameters, thereby reducing the model size while maintaining the high accuracy in contrast to conventional CNN models. In addition, we also evaluate the performance of our proposed model via conducting experiments at a realistic MEC platform. Specifically, experimental results at this MEC platform show that our model can maintain the high accuracy while preserving the portable model size.

Original languageEnglish
Article number67
Number of pages20
JournalACM Transactions on Intelligent Systems and Technology
Issue number6
Publication statusPublished - Nov 2019

Scopus Subject Areas

  • Theoretical Computer Science
  • Artificial Intelligence

User-Defined Keywords

  • Convolutional neural network
  • Cyber physical systems
  • Factorization
  • Jetson TX2 module
  • Mobile edge computing
  • Model compression


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