Graduation Semester and Year
Spring 2026
Language
English
Document Type
Thesis
Degree Name
Master of Science in Computer Science
Department
Computer Science and Engineering
First Advisor
Parwez,Md Salik
Second Advisor
Roy,Debashri
Third Advisor
Olufowobi,Habeeb
Abstract
Digital twin technology has emerged as a foundational paradigm for enabling real-time monitoring, analysis, and control in Internet of Things (IoT) systems by maintaining virtual representations of physical processes. Its effectiveness, however, critically depends on timely and accurate synchronization between distributed sensing devices and their corresponding digital counterparts. Frequent synchronization improves reconstruction fidelity and system responsiveness but incurs significant communication energy consumption and network latency. In contrast, infrequent synchronization conserves communication resources but can lead to stale or inaccurate digital twin states, particularly in environments with rapidly changing dynamics. These opposing effects give rise to a fundamental trade-off among energy efficiency, accuracy, and timeliness. This thesis develops a unified framework for analyzing synchronization strategies in digital twin–enabled IoT systems, where performance is evaluated using the eTUNE metric that integrates energy consumption, reconstruction error, and latency into a single interpretable score. Building on this framework, a drift-adaptive synchronization mechanism is proposed to dynamically adjust update behavior based on observed signal variation, increasing update frequency under rapid changes while suppressing unnecessary transmissions during stable periods. Threshold bounding and staleness control are incorporated to ensure robust operation across diverse scenarios. The framework is evaluated using both real-world crowd-sensing traces and synthetic signal models. The results show that conventional synchronization strategies such as periodic, event-driven, and hybrid are effective only within specific operating regimes and require careful parameter tuning, whereas the proposed adaptive mechanism achieves consistent and favorable energy–fidelity–latency trade-offs across a wide range of conditions without manual configuration. These findings provide both theoretical insights and practical guidelines for designing scalable and energy-efficient digital twin systems in dynamic IoT environments, highlighting the importance of adaptive, data-driven synchronization in next-generation cyber–physical systems.
Keywords
Digital Twin Synchronization, Adaptive IoT Systems, Energy-Efficient Communication, Dynamic Update Policies, Reconstruction Error Minimization, Drift Estimation, Real-Time Synchronization, Latency-Constrained IoT, eTUNE Performance Metric, Resource-Aware IoT Networks
Disciplines
Digital Communications and Networking
License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Zehra, Uzma, "Adaptive Synchronization in Digital Twin–Enabled IoT Systems: A Unified Framework for Energy, Fidelity, and Latency Trade-offs" (2026). Computer Science and Engineering Theses. 1.
https://mavmatrix.uta.edu/cse_theses2/1