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Mobility-Aware Cooperative Service Caching for Mobile Augmented Reality Services in Mobile Edge Computing

  • Harbin Institute of Technology
  • School of Computer Science and Technology, Harbin Institute of Technology
  • Peng Cheng Laboratory
  • Harbin Engineering University

Research output: Contribution to journalArticlepeer-review

Abstract

Mobile edge computing (MEC) plays a significant role in reducing network delay for Mobile Augmented Reality (MAR) services by caching these services close to the User Equipments (UEs). These MAR services collect UEs' network traffic and orientation information, and generate the service results back to UEs. However, the UE's mobility features change network traffic and orientation, negatively impacting MAR services' access frequencies and service preferences. Moreover, the changed access frequencies also influence the workload of cached MAR services, resulting in the uneven workload of edge servers. Therefore, this paper formalizes cooperative service caching based on UEs' location and orientation to optimize network delay and response fairness in MEC environments. To solve the problem, we propose a Service Caching strategy based on Regional Mobility features Awareness (SCRMA) algorithm, which consists of two stages. Firstly, the Regional Mobility features Awareness (RMA) algorithm perceives the user mobility features and service preferences, which provides a prerequisite for determining service caching strategy. Then, a Service Caching strategy based on a Genetic Algorithm (SCGA) is proposed to optimize network delay and response fairness. The simulation experiment on a real dataset shows that our service caching strategy averagely reduces network delay, fairness factor, and total cost by 11.49%, 33.24%, and 17.86% compared with the existing algorithms, respectively.

Original languageEnglish
Pages (from-to)17543-17557
Number of pages15
JournalIEEE Transactions on Vehicular Technology
Volume73
Issue number11
DOIs
StatePublished - 2024
Externally publishedYes

Keywords

  • Edge computing
  • genetic algorithm
  • mobile augmented reality
  • service caching

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