Optimal Placement of Social Digital Twins in Edge IoT Networks
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Otros documentos de la autoría: Chukhno, Olga; Chukhno, Nadezhda; ARANITI, Giuseppe; CAMPOLO, Claudia; Iera, Antonio; Molinaro, Antonella
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Optimal Placement of Social Digital Twins in Edge IoT NetworksAutoría
Fecha de publicación
2020Editor
MDPIISSN
1424-8220Cita bibliográfica
CHUKHNO, Olga, et al. Optimal Placement of Social Digital Twins in Edge IoT Networks. Sensors, 2020, vol. 20, núm. 21, p. 6181Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.mdpi.com/1424-8220/20/21/6181Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
In next-generation Internet of Things (IoT) deployments, every object such as a wearable
device, a smartphone, a vehicle, and even a sensor or an actuator will be provided with a digital
counterpart (twin) with the ... [+]
In next-generation Internet of Things (IoT) deployments, every object such as a wearable
device, a smartphone, a vehicle, and even a sensor or an actuator will be provided with a digital
counterpart (twin) with the aim of augmenting the physical object’s capabilities and acting on
its behalf when interacting with third parties. Moreover, such objects can be able to interact and
autonomously establish social relationships according to the Social Internet of Things (SIoT) paradigm.
In such a context, the goal of this work is to provide an optimal solution for the social-aware placement
of IoT digital twins (DTs) at the network edge, with the twofold aim of reducing the latency (i) between
physical devices and corresponding DTs for efficient data exchange, and (ii) among DTs of friend
devices to speed-up the service discovery and chaining procedures across the SIoT network. To this
aim, we formulate the problem as a mixed-integer linear programming model taking into account
limited computing resources in the edge cloud and social relationships among IoT devices. [-]
Publicado en
Sensors, 2020, vol. 20, núm. 21, p. 6181Proyecto de investigación
The authors gratefully acknowledge funding from European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie grant agreement No. 813278Derechos de acceso
info:eu-repo/semantics/openAccess
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