Energy-efficient computation offloading with privacy preservation for edge computing-enabled 5G networks

Xihua Liu, Xiaolong Xu, Yuan Yuan, Xuyun Zhang, Wanchun Dou

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

Nowadays, due to the developments in wireless communication, the amount of data produced by mobile devices is increasing rapidly. The mobile devices can hardly handle these data immediately as they have limitations on their computing power. In edge computing, the computing tasks can be offloaded from the mobile devices to nearby edge nodes (ENs) for implementing. Combined with 5G networks, the computing tasks can be offloaded to the central units (CUs), enhanced into ENs, or the cloud infrastructure via distributed units (DUs) for processing. In this way, the above phenomenon will be effectively released. However, how to select the appropriate ENs for executing, aiming to keep a balance between the load balance and the energy consumption, is still a big problem waiting to be solved. In this paper, an optimization problem is formulated to improve the load balance and reduce the energy consumption of all the ENs for edge computing-enabled 5G networks while considering the privacy conflicts and time consumption. Then, an energy-efficient computation offloading method with privacy preservation, named ECOP, is proposed. Finally, experimental results and evaluations confirm our proposed method is feasible.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Congress on Cybermatics
Subtitle of host publication12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages176-181
Number of pages6
ISBN (Electronic)9781728129808
ISBN (Print)9781728129815
DOIs
Publication statusPublished - 1 Jul 2019
Externally publishedYes
Event12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019 - Atlanta, United States
Duration: 14 Jul 201917 Jul 2019

Publication series

NameProceedings - 2019 IEEE International Congress on Cybermatics: 12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019

Conference

Conference12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019
CountryUnited States
CityAtlanta
Period14/07/1917/07/19

Keywords

  • 5G
  • edge computing
  • edge nodes
  • energy consumption
  • load balance

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