TY - JOUR
T1 - Key Advances in Pervasive Edge Computing for Industrial Internet of Things in 5G and Beyond
AU - Narayanan, Arun
AU - Sousa de Sena, Arthur
AU - Gutierrez-Rojas, Daniel
AU - Carrillo Melgarejo, Dick
AU - Hussain, Hafiz Majid
AU - Ullah, Mehar
AU - Bayhan, Suzan
AU - Nardelli, Pedro H.J.
N1 - Funding Information:
This work was supported in part by the Academy of Finland through the ee-IoT Project under Grant n.319009, the FIREMAN Consortium under Grant CHIST-ERA/n.326270, and the EnergyNet Research Fellowship under Grant n.321265/n.328869.
Publisher Copyright:
© 2013 IEEE.
PY - 2020/11/25
Y1 - 2020/11/25
N2 - This article surveys emerging technologies related to pervasive edge computing (PEC) for industrial internet-of-things (IIoT) enabled by fifth-generation (5G) and beyond communication networks. PEC encompasses all devices that are capable of performing computational tasks locally, including those at the edge of the core network (edge servers co-located with 5G base stations) and in the radio access network (sensors, actuators, etc.). The main advantages of this paradigm are core network offloading (and benefits therefrom) and low latency for delay-sensitive applications (e.g., automatic control). We have reviewed the state-of-the-art in the PEC paradigm and its applications to the IIoT domain, which have been enabled by the recent developments in 5G technology. We have classified and described three important research areas related to PEC—distributed artificial intelligence methods, energy efficiency, and cyber security. We have also identified the main open challenges that must be solved to have a scalable PEC-based IIoT network that operates efficiently under different conditions. By explaining the applications, challenges, and opportunities, our paper reinforces the perspective that the PEC paradigm is an extremely suitable and important deployment model for industrial communication networks, considering the modern trend toward private industrial 5G networks with local operations and flexible management.
AB - This article surveys emerging technologies related to pervasive edge computing (PEC) for industrial internet-of-things (IIoT) enabled by fifth-generation (5G) and beyond communication networks. PEC encompasses all devices that are capable of performing computational tasks locally, including those at the edge of the core network (edge servers co-located with 5G base stations) and in the radio access network (sensors, actuators, etc.). The main advantages of this paradigm are core network offloading (and benefits therefrom) and low latency for delay-sensitive applications (e.g., automatic control). We have reviewed the state-of-the-art in the PEC paradigm and its applications to the IIoT domain, which have been enabled by the recent developments in 5G technology. We have classified and described three important research areas related to PEC—distributed artificial intelligence methods, energy efficiency, and cyber security. We have also identified the main open challenges that must be solved to have a scalable PEC-based IIoT network that operates efficiently under different conditions. By explaining the applications, challenges, and opportunities, our paper reinforces the perspective that the PEC paradigm is an extremely suitable and important deployment model for industrial communication networks, considering the modern trend toward private industrial 5G networks with local operations and flexible management.
KW - Edge computing
KW - Industrial Internet of Things
KW - 5G network
KW - Energy efficiency
KW - Artificial intelligence
KW - Cyber security
U2 - 10.1109/ACCESS.2020.3037717
DO - 10.1109/ACCESS.2020.3037717
M3 - Article
SN - 2169-3536
VL - 8
SP - 206734
EP - 206754
JO - IEEE Access
JF - IEEE Access
M1 - 9257390
ER -