An Adaptive Computation Offloading Mechanism for Mobile Health Applications

Shijie Dai, Minghui Li Wang, Zhibin Gao, Lianfen Huang, Xiaojiang Du, Mohsen Guizani

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Recently, research intergrading medicine and Artificial Intelligence has attracted extensive attention. Mobile health has emerged as a promising paradigm for improving people's work and life in the future. However, high mobility of mobile devices and limited resources pose challenges for users to deal with the applications in mobile health that require large amount of computational resources. In this paper, a novel computation offloading mechanism is proposed in the environments combining of the Internet of Vehicles and Multi-Access Edge Computing. Through the proposed mechanism, mobile health applications are divided into several parts and can be offloaded to appropriate nearby vehicles while meeting the requirements of application completion time, energy consumption, and resource utilization. A particle swarm optimization based approach is proposed to optimize the the aforementioned computation offloading problem in a specific medical application. Evaluations of the proposed algorithms against local computing method serves as baseline method are conducted via extensive simulations. The average task completion time saved by our proposed task allocation scheme increases continually compared with the local solution. Specially, the global resource utilization rate increased from 71.8% to 94.5% compared with the local execution time.

Original languageEnglish
Article number8908803
Pages (from-to)998-1007
Number of pages10
JournalIEEE Transactions on Vehicular Technology
Volume69
Issue number1
DOIs
StatePublished - Jan 2020

Keywords

  • Computation offloading
  • disaster medicine
  • internet of vehicles
  • mobile health
  • multi-access edge computing

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