2022
Chukhno, Olga; Chukhno, Nadezhda; Araniti, Giuseppe; Campolo, Claudia; Iera, Antonio; Molinaro, Antonella
Placement of Social Digital Twins at the Edge for Beyond 5G IoT Networks Journal Article
In: IEEE Internet of Things Journal , vol. 9, no. 23, pp. 23927 - 23940, 2022, ISSN: 2327-4662, (2022-38).
Abstract | Links | BibTeX | Tags: A-wear, digital twin, Internet of things
@article{Chukhno2022c,
title = {Placement of Social Digital Twins at the Edge for Beyond 5G IoT Networks},
author = {Olga Chukhno and Nadezhda Chukhno and Giuseppe Araniti and Claudia Campolo and Antonio Iera and Antonella Molinaro},
doi = {https://doi.org/10.1109/JIOT.2022.3190737},
issn = {2327-4662},
year = {2022},
date = {2022-12-01},
urldate = {2022-12-01},
journal = {IEEE Internet of Things Journal },
volume = {9},
number = {23},
pages = {23927 - 23940},
publisher = {IEEE},
abstract = {As the fifth-generation (5G) and beyond (5G+/6G) networks move forward, and a wide variety of new advanced Internet of Things (IoT) applications are offered, effective methodologies for discovering time-relevant information, services, and resources are being demanded. To this end, computing-, storage-, and battery-constrained IoT devices are progressively augmented via digital twins (DTs) hosted on edge servers. According to recent research results, a further feature these devices may acquire is social behavior; this latter offers enormous possibilities for fast and trustworthy service discovery, although it requires new orchestration policies of DTs at the network edge. This work addresses the dynamic placement of DTs with social capabilities [social digital twins (SDTs)] at the edge, by providing an optimal solution under IoT device mobility and by accounting for edge network deployment specifics, types of devices, and their social peculiarities. The optimization problem is formulated as a particular case of the quadratic assignment problem (QAP); also, an approximation algorithm is proposed and two relaxation techniques are applied to reduce computation complexity. Results show that the proposed placement policy ensures a latency among SDTs up to 1.4 times lower than the one obtainable with a traditional proximity-based only placement while still guaranteeing appropriate proximity between physical devices and their virtual counterparts. Moreover, the proposed heuristic closely approximates the optimal solution while guaranteeing the lowest computational time.},
note = {2022-38},
keywords = {A-wear, digital twin, Internet of things},
pubstate = {published},
tppubtype = {article}
}
As the fifth-generation (5G) and beyond (5G+/6G) networks move forward, and a wide variety of new advanced Internet of Things (IoT) applications are offered, effective methodologies for discovering time-relevant information, services, and resources are being demanded. To this end, computing-, storage-, and battery-constrained IoT devices are progressively augmented via digital twins (DTs) hosted on edge servers. According to recent research results, a further feature these devices may acquire is social behavior; this latter offers enormous possibilities for fast and trustworthy service discovery, although it requires new orchestration policies of DTs at the network edge. This work addresses the dynamic placement of DTs with social capabilities [social digital twins (SDTs)] at the edge, by providing an optimal solution under IoT device mobility and by accounting for edge network deployment specifics, types of devices, and their social peculiarities. The optimization problem is formulated as a particular case of the quadratic assignment problem (QAP); also, an approximation algorithm is proposed and two relaxation techniques are applied to reduce computation complexity. Results show that the proposed placement policy ensures a latency among SDTs up to 1.4 times lower than the one obtainable with a traditional proximity-based only placement while still guaranteeing appropriate proximity between physical devices and their virtual counterparts. Moreover, the proposed heuristic closely approximates the optimal solution while guaranteeing the lowest computational time.
2020
Chukhno, Olga; Chukhno, Nadezhda; Araniti, Giuseppe; Campolo, Claudia; Iera, Antonio; Molinaro, Antonella
Optimal Placement of Social Digital Twins in Edge IoT Networks Journal Article
In: Sensors, vol. 20, no. 21, pp. 6181, 2020, ISSN: 1424-8220, (2020-56).
Abstract | Links | BibTeX | Tags: A-wear, digital twin, Internet of things
@article{Chukhno2020a,
title = {Optimal Placement of Social Digital Twins in Edge IoT Networks},
author = {Olga Chukhno and Nadezhda Chukhno and Giuseppe Araniti and Claudia Campolo and Antonio Iera and Antonella Molinaro},
doi = {https://doi.org/10.3390/s20216181},
issn = {1424-8220},
year = {2020},
date = {2020-10-30},
urldate = {2020-10-30},
journal = {Sensors},
volume = {20},
number = {21},
pages = {6181},
publisher = {IEEE},
abstract = {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.},
note = {2020-56},
keywords = {A-wear, digital twin, Internet of things},
pubstate = {published},
tppubtype = {article}
}
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.