Optimal Placement of Social Digital Twins in Edge IoT Networks
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Altres documents de l'autoria: 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 NetworksAutoria
Data de publicació
2020Editor
MDPIISSN
1424-8220Cita bibliogràfica
CHUKHNO, Olga, et al. Optimal Placement of Social Digital Twins in Edge IoT Networks. Sensors, 2020, vol. 20, núm. 21, p. 6181Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://www.mdpi.com/1424-8220/20/21/6181Versió
info:eu-repo/semantics/publishedVersionParaules clau / Matèries
Resum
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. [-]
Publicat a
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. 813278Drets d'accés
info:eu-repo/semantics/openAccess
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