Mobility-Aware Utility Maximization in Digital Twin-Enabled Serverless Edge Computing

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

3 Scopus Citations
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Author(s)

  • Jing Li
  • Song Guo
  • Quan Chen
  • Wenchao Xu
  • Kang Wei

Detail(s)

Original languageEnglish
Pages (from-to)1837-1851
Journal / PublicationIEEE Transactions on Computers
Volume73
Issue number3
Online published16 Apr 2024
Publication statusPublished - Jul 2024

Abstract

Driven by data and models, the digital twin technique presents a new concept of optimizing system design, process monitoring, decision-making and more, through performing comprehensive virtual-reality interaction and continuous mapping. By introducing serverless computing to Mobile Edge Computing (MEC) environments, the emerging serverless edge computing paradigm facilitates the communication-efficient digital twin services and promises agile, fine-grained and cost-efficient provisioning of limited edge resources, where serverless functions are implemented by containers in cloudlets (edge servers). However, the nonnegligible cold start delay of containers deteriorates the responsiveness of digital twin services dramatically and the perceived user service experience. In this paper, we investigate delay-sensitive query service provisioning in digital twin-empowered serverless edge computing by considering user mobility. With digital twins of users deployed in the remote cloud, referred to as primary digital twins, we deploy their digital twin replicas based on serverless functions in cloudlets to mitigate the query service delay while enhancing user service satisfaction that is expressed as a utility function. We study two optimization problems with the aim of maximizing the accumulative utility gain: the digital twin replica placement problem per time slot, and the dynamic digital twin replica placement problem over a finite time horizon. We first formulate an Integer Linear Program (ILP) solution for the digital twin replica placement problem when the problem size is small; otherwise, we propose an approximation algorithm for the problem with a provable approximation ratio. We then design an online algorithm for the dynamic digital twin replica placement problem, and a performance-guaranteed online algorithm for a special case of the problem by assuming each user issues a query at each time slot. Finally, we evaluate the performance of the proposed algorithms for placing digital twin replicas in MEC networks through simulations. The results demonstrate the proposed algorithms are promising, outperforming their counterparts. © 2024 IEEE.

Research Area(s)

  • approximation algorithm, Approximation algorithms, Computers, Containers, delay-sensitive service, Delays, Digital twin, Digital twins, Edge computing, Heuristic algorithms, mobile edge computing, online algorithm, resource allocation and optimization, serverless computing, user mobility, user service satisfaction, utility maximization

Bibliographic Note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Citation Format(s)

Mobility-Aware Utility Maximization in Digital Twin-Enabled Serverless Edge Computing. / Li, Jing; Guo, Song; Liang, Weifa et al.
In: IEEE Transactions on Computers, Vol. 73, No. 3, 07.2024, p. 1837-1851.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review