Proximity-based service discovery for distributed digital twin systems
Abstract Over the past decade, there has been a significant increase in interest in digital twin (DT) technology in a variety of domains. While research on DTs of single assets was initially prevalent, there has been a notable shift towards distributed systems of DTs, which connect to each other to...
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| Format: | Article |
| Language: | English |
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Springer
2025-02-01
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| Series: | Discover Internet of Things |
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| Online Access: | https://doi.org/10.1007/s43926-025-00103-x |
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| author | Kurt Rothermel Otthein Herzog Siegfried Wu Zhiqiang |
| author_facet | Kurt Rothermel Otthein Herzog Siegfried Wu Zhiqiang |
| author_sort | Kurt Rothermel |
| collection | DOAJ |
| description | Abstract Over the past decade, there has been a significant increase in interest in digital twin (DT) technology in a variety of domains. While research on DTs of single assets was initially prevalent, there has been a notable shift towards distributed systems of DTs, which connect to each other to collaborate. Typically, collaboration is enabled by DTs providing services that can be consumed by other DTs. In service-oriented systems, a service is typically identified by type information. However, this is not sufficient in distributed DT systems, where DTs associated with different physical entities may provide the same type of service. Consequently, selecting the appropriate service depends not only on the service type, but also on the associated physical entity. However, requiring DTs to know the mapping of services to their physical environment is not feasible for large dynamic systems. This paper presents a novel proximity-based service discovery method that allows DTs to select services based on service type and their proximity to other objects. That is, service specifications are fully abstracted from the mapping of services to physical objects, relieving DTs from maintaining information about this mapping. Furthermore, service discovery is robust to changes in the physical environment and service population. The proposed service discovery method has been implemented on top of a spatial DBMS. We argue that this implementation is optimal in terms of network utilization and latency, and perform comprehensive evaluations to show the performance of discovery queries as a function of their complexity. |
| format | Article |
| id | doaj-art-22acb9e7ca814c40bb871f79fc104e09 |
| institution | DOAJ |
| issn | 2730-7239 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Internet of Things |
| spelling | doaj-art-22acb9e7ca814c40bb871f79fc104e092025-08-20T03:10:52ZengSpringerDiscover Internet of Things2730-72392025-02-015112410.1007/s43926-025-00103-xProximity-based service discovery for distributed digital twin systemsKurt Rothermel0Otthein Herzog1Siegfried Wu Zhiqiang2Institute Of Parallel and Distributed Systems, University of StuttgartCollege of Architecture and Urban Planning, Tongji UniversityCollege of Architecture and Urban Planning, Tongji UniversityAbstract Over the past decade, there has been a significant increase in interest in digital twin (DT) technology in a variety of domains. While research on DTs of single assets was initially prevalent, there has been a notable shift towards distributed systems of DTs, which connect to each other to collaborate. Typically, collaboration is enabled by DTs providing services that can be consumed by other DTs. In service-oriented systems, a service is typically identified by type information. However, this is not sufficient in distributed DT systems, where DTs associated with different physical entities may provide the same type of service. Consequently, selecting the appropriate service depends not only on the service type, but also on the associated physical entity. However, requiring DTs to know the mapping of services to their physical environment is not feasible for large dynamic systems. This paper presents a novel proximity-based service discovery method that allows DTs to select services based on service type and their proximity to other objects. That is, service specifications are fully abstracted from the mapping of services to physical objects, relieving DTs from maintaining information about this mapping. Furthermore, service discovery is robust to changes in the physical environment and service population. The proposed service discovery method has been implemented on top of a spatial DBMS. We argue that this implementation is optimal in terms of network utilization and latency, and perform comprehensive evaluations to show the performance of discovery queries as a function of their complexity.https://doi.org/10.1007/s43926-025-00103-xInternet of thingsCyber-physical systemsDigital twinsService discovery |
| spellingShingle | Kurt Rothermel Otthein Herzog Siegfried Wu Zhiqiang Proximity-based service discovery for distributed digital twin systems Discover Internet of Things Internet of things Cyber-physical systems Digital twins Service discovery |
| title | Proximity-based service discovery for distributed digital twin systems |
| title_full | Proximity-based service discovery for distributed digital twin systems |
| title_fullStr | Proximity-based service discovery for distributed digital twin systems |
| title_full_unstemmed | Proximity-based service discovery for distributed digital twin systems |
| title_short | Proximity-based service discovery for distributed digital twin systems |
| title_sort | proximity based service discovery for distributed digital twin systems |
| topic | Internet of things Cyber-physical systems Digital twins Service discovery |
| url | https://doi.org/10.1007/s43926-025-00103-x |
| work_keys_str_mv | AT kurtrothermel proximitybasedservicediscoveryfordistributeddigitaltwinsystems AT ottheinherzog proximitybasedservicediscoveryfordistributeddigitaltwinsystems AT siegfriedwuzhiqiang proximitybasedservicediscoveryfordistributeddigitaltwinsystems |