Hybrid quantum-behaved particle swarm optimization for mobile-edge computation offloading in internet of things

Shijie Dai, Minghui Liwang, Yang Liu, Zhibin Gao, Lianfen Huang, Xiaojiang Du

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Mobile edge computing (MEC) is a technology that transfers resource to the edge of network, which spares more attention to giving users easier access to network and computation resources. Due to the large amount of data computation needed for devices in Internet of Things, MEC technology is applied to improve computing efficiency. Though MEC can be applied to the Internet of Things, it needs further consideration on how to efficiently and reasonably allocate computing resources, and how to minimize the computing time of all users. This paper proposes a computing resources allocation scheme based on hybrid quantum-behaved particle swarm optimization. Simulation experiments with the network environment based on the Internet of Things is carried out. The results show that this algorithm can accelerate the whole computing process and reduce the number of iterations.

Original languageEnglish
Title of host publicationMobile Ad-hoc and Sensor Networks - 13th International Conference, MSN 2017, Revised Selected Papers
EditorsLiehuang Zhu, Sheng Zhong
Pages350-364
Number of pages15
DOIs
StatePublished - 2018
Event13th International Conference on Mobile Ad-hoc and Sensor Networks, MSN 2017 - Beijing, China
Duration: 17 Dec 201720 Dec 2017

Publication series

NameCommunications in Computer and Information Science
Volume747
ISSN (Print)1865-0929

Conference

Conference13th International Conference on Mobile Ad-hoc and Sensor Networks, MSN 2017
Country/TerritoryChina
CityBeijing
Period17/12/1720/12/17

Keywords

  • Internet of things
  • Mobile edge computing
  • Offloading

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