Cost-minimized User Association and Partial Offloading for Dependent Tasks in Hybrid Cloud-edge Systems

Haitao Yuan, Qinglong Hu, Meijia Wang, Jing Bi, Meng Chu Zhou

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

3 Scopus citations

Abstract

Edge nodes (ENs) in mobile edge computing can support current delay-sensitive applications of the Industrial Internet of Things. ENs are deployed in the network edge and can execute computational tasks offloaded from users' mobile devices (MDs) in a timely way. However, their computing and communication resources are limited and cannot execute all offloaded tasks. Thus, a cloud data center (CDC) is highly needed and hybrid cloud-edge systems emerge to provide low-delay services. This work investigates a joint optimization problem of task offloading, task partitioning, and user association to minimize the total cost of the system. This work focuses on applications that can be split into multiple dependent subtasks, each of which can be completed in MDs, ENs, and CDC. Specifically, a mixed integer nonlinear program is formulated to minimize the total cost. Then, a hybrid algorithm named Genetic Simulated-annealing-based Particle Swarm Optimizer (GSPSO) is designed to solve it. GSPSO yields a close-to-optimal strategy to jointly optimize connections among MDs and ENs, and allocation ratios among MDs, ENs, and CDC. Experimental results demonstrate that compared with benchmark methods, GSPSO decreases the total cost while fully meeting the completion time requirements of user tasks.

Original languageEnglish (US)
Title of host publication2022 IEEE 18th International Conference on Automation Science and Engineering, CASE 2022
PublisherIEEE Computer Society
Pages1059-1064
Number of pages6
ISBN (Electronic)9781665490429
DOIs
StatePublished - 2022
Event18th IEEE International Conference on Automation Science and Engineering, CASE 2022 - Mexico City, Mexico
Duration: Aug 20 2022Aug 24 2022

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2022-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference18th IEEE International Conference on Automation Science and Engineering, CASE 2022
Country/TerritoryMexico
CityMexico City
Period8/20/228/24/22

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Keywords

  • Edge computing
  • cloud computing
  • computation offloading
  • genetic algorithm
  • particle swarm optimization

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