Improving the Freshness of Digital Twins in Edge Computing
Abstract
With the advent of Mobile Edge Computing (MEC) that shifts powerful computing resource from remote data centers to the network edge, Digital Twins (DTs) have emerged as a promising technology to provide comprehensive descriptions of physical objects in cyberspace with real-time interactions. Recent advancements of the Internet of Things (IoT) have contributed abundant and continuous data to the explosion of DTs, spurring the need to address the freshness of DTs through timely synchronizations. In this paper, we investigate innovative methodologies to improve the freshness of DTs while minimizing the cost of diverse resources consumed for improving freshness. Specifically, we first formulate a novel optimization problem: the DT freshness optimization problem. Next, we provide an Integer Linear Program (ILP) solution for the DT freshness optimization problem when the problem size is small; and devise a randomized algorithm at the expense of bounded resource violations, otherwise. We finally evaluate the performance of our algorithm through simulations. The simulation results show that our algorithm is promising.
Recommended Citation
J. Li et al., "Improving the Freshness of Digital Twins in Edge Computing," Lecture Notes in Computer Science, vol. 15687 LNCS, pp. 74 - 86, Springer, Jan 2025.
The definitive version is available at https://doi.org/10.1007/978-981-96-8728-2_7
Department(s)
Computer Science
Keywords and Phrases
Cost modelling; Digital Twin (DT); DT synchronization; Mobile edge computing; Online and approximation algorithms; Resource allocation
International Standard Book Number (ISBN)
978-981968727-5
International Standard Serial Number (ISSN)
1611-3349; 0302-9743
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Springer, All rights reserved.
Publication Date
01 Jan 2025
Comments
Research Grants Council, University Grants Committee, Grant CityU PDFS2425-1S02