Learning for Smart Edge: Cognitive Learning-Based Computation Offloading

Yixue Hao, Yinging Jiang, M. Shamim Hossain, Mohammed F. Alhamid, Syed Umar Amin

Research output: Contribution to journalJournal articlepeer-review

1 Scopus citations


With the development of intelligent applications, more and more intelligent applications are computation intensive, data intensive and delay sensitive. Compared with traditional cloud computing, edge computing can reduce communication delay by offloading computing tasks to edge cloud. Furthermore, with the complexity of computing scenarios in edge cloud, deep learning based on computation offloading scheme has attracted wide attention. However, all the learning-based offloading scheme does not consider the where and how to run the offloading scheme itself. Thus, in this paper, we consider the problem of running the learning-based computation offloading scheme for the first time and propose the learning for smart edge architecture. Then, we give the computation offloading optimization problem of mobile devices under multi-user and multi edge cloud scenarios. Furthermore, we propose cognitive learning-based computation offloading (CLCO) scheme for this problem. Finally, experimental results show that compared with other offloading schemes, the CLCO scheme has lower task duration and energy consumption.

Original languageEnglish
Pages (from-to)1016-1022
Number of pages7
JournalMobile Networks and Applications
Issue number3
StatePublished - 1 Jun 2020


  • Cognitive learning
  • Communication
  • Computation offloading
  • Edge computing


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