Smart City Gnosys
Smart city article details
| Title | Multiple Service Model Refreshments In Digital Twin-Empowered Edge Computing |
|---|---|
| ID_Doc | 38627 |
| Authors | Liang X.; Liang W.; Xu Z.; Zhang Y.; Jia X. |
| Year | 2024 |
| Published | IEEE Transactions on Services Computing, 17, 5 |
| DOI | http://dx.doi.org/10.1109/TSC.2023.3341988 |
| Abstract | Mobile Edge Computing (MEC) has emerged as a promising platform to provide various services for mobile applications at the edge of core networks while meeting stringent service delay requirements of users. Digital twin (DT) that is a mirror of a physical object in cyberspace now becomes a key player in smart cities and the Metaverse, which can be used to simulate or predict the behaviours of the object in future. To enable such a simulation or predication to be more accurate and robust, the state of the digital twin needs to be synchronized (updated) with its object quite often. The quality of inference services in a DT-empowered MEC network usually is determined by the state freshness of service models, while the quality of a service model further is determined by the state freshness of its source DT data. It is vital to refresh the states of service models frequently in order to provide high quality inference services. In this article, we study how to maximize the state freshness of both digital twins and a set of inference service models that are built upon digital twins in an MEC network, while the state freshness of a DT or a service model is achieved through frequent synchronizations between the DT and its physical object. Specifically, we first study a novel cost-aware average model freshness maximization problem with the aim to maximize the average freshness of the states of inference service models while minimizing the cost of achieving the model freshness, and show the NP-hardness of the problem. We then formulate an integer linear programming solution for the offline version of the problem, and devise a performance-guaranteed approximation algorithm for a special case of problem when the monitoring period consists of a single time slot only. Also, we develop an efficient online algorithm for the problem through scheduling objects to upload their update data to their digital twins in the network at each time slot efficiently. We finally evaluate the performance of the proposed algorithms through simulations. Simulation results demonstrate that the proposed algorithms are promising. © 2008-2012 IEEE. |
| Author Keywords | Approximation algorithms; digital twin state updating; minimum-cost generalized assignment problem; mobile edge computing (MEC); scheduling algorithms; state refreshment of service models; tradeoffs between the state freshness of service models and the update cost |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
18054  | 0.883 | Zhang Y.; Wang L.; Liang W. | Deep Reinforcement Learning For Mobility-Aware Digital Twin Migrations In Edge Computing | IEEE Transactions on Services Computing, 18, 2 (2025) |
| 14480 | 0.872 | Ranjbaran S.; Amadeo M.; Marche C.; Ruggeri G.; Sinha A.; Nitti M. | Cloud-Edge Resource Management And Migration: Leveraging Online Learning For Digital Twin Re-Placement | 2024 IEEE 10th World Forum on Internet of Things, WF-IoT 2024 (2024) |
| 1481 | 0.867 | Bozkaya E. | A Digital Twin Framework For Edge Server Placement In Mobile Edge Computing | 4th International Informatics and Software Engineering Conference - Symposium Program, IISEC 2023 (2023) |
| 10281 | 0.865 | Linkevics G.; Mosans G.; Kampars J.; Gulbe R. | Architectural Requirements For Digital Twin Development Platform: A Review Of Scientific Literature And Practical Considerations | 2025 IEEE 12th Workshop on Advances in Information, Electronic and Electrical Engineering, AIEEE 2025 - Proceedings (2025) |
| 54438 | 0.859 | Alfahad S.; Wang Q.; Anagnostopoulos C.; Kolomvatsos K. | Task Offloading In Mobile Edge Computing Using Cost-Based Discounted Optimal Stopping | Open Computer Science, 14, 1 (2024) |
| 9383 | 0.855 | Rinaldi S.; Iacono S.D.; Bellagente P.; Pasetti M. | Analysis Of Time Synchronization Challenges In Digital Twins For Edge-Enabled Data Centers In Smart Cities Scenario | Proceedings - 33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2025 (2025) |
| 20632 | 0.852 | Kang M.; Li X.; Ji H.; Zhang H. | Distributed Edge Cooperation And Data Collection For Digital Twins Of Wide-Areas | China Communications, 20, 8 (2023) |
| 47145 | 0.851 | Vodyaho A.; Delhibabu R.; Ignatov D.I.; Zhukova N. | Run Time Dynamic Digital Twins And Dynamic Digital Twins Networks | Future Generation Computer Systems, 172 (2025) |