TwinSync: A Digital Twin Synchronization Protocol for Bandwidth-Limited IoT Applications

Deepti Kalasapura, Jinyang Li, Shengzhong Liu, Yizhuo Chen, Ruijie Wang, Tarek Abdelzaher, Matthew Caesar, Joydeep Bhattacharyya, Jae Kim, Guijun Wang, Greg Kimberly, Josh Eckhardt, Denis Osipychev

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

Abstract

Digital Twins are evolving as a key component in modern systems with diverse applications like remote prognostics, optimizing run-time operation, anomaly detection, and more. The essential elements of a digital twin are a virtual representation, a physical asset, and the transfer of data/information between the two. IoT deployments are generally characterized by resource constraints, making synchronization of digital twins with IoT devices more challenging. There is a pressing need to optimize the bandwidth of the data transferred between the system and the twin, while ensuring that the twin is able to capture selected key aspects of the current operational state accurately. In this paper, we present TwinSync, a framework that can be utilized to construct flexible real-time representations of deployed IoT systems and efficiently synchronize relevant system states with the twin, over a communication bottleneck, within a configurable application-specific notion of error (henceforth referred to as approximate synchronization). Our approach is optimized to achieve data transfers utilizing less bandwidth without compromising the ability of the twin to replicate real-time system states within the specified approximate synchronization semantics. We evaluate the efficacy of TwinSync's synchronization by conducting both a synthetic analysis and a case study based on a real-life application prototype. Our evaluation indicates that using TwinSync can provide the same or greater accuracy (in many cases) while sending significantly fewer bytes than a bandwidth-insensitive synchronization approach. The result is attributed to a more judicial selection of data to transmit over bottlenecks, compared to bandwidth-insensitive approaches.

Original languageEnglish (US)
Title of host publicationICCCN 2023 - 2023 32nd International Conference on Computer Communications and Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350336184
DOIs
StatePublished - 2023
Externally publishedYes
Event32nd International Conference on Computer Communications and Networks, ICCCN 2023 - Honolulu, United States
Duration: Jul 24 2023Jul 27 2023

Publication series

NameProceedings - International Conference on Computer Communications and Networks, ICCCN
Volume2023-July
ISSN (Print)1095-2055

Conference

Conference32nd International Conference on Computer Communications and Networks, ICCCN 2023
Country/TerritoryUnited States
CityHonolulu
Period7/24/237/27/23

Keywords

  • Data Synchronization
  • Digital Twinning
  • Internet of Things
  • Optimization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Software

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