Physical-layer secure hybrid task scheduling and resource management for fog computing IoT networks

doi:10.23919/JSEE.2024.000052

Journal of Systems Engineering and Electronics ›› 2025, Vol. 36 ›› Issue (5): 1146-1160.doi: 10.23919/JSEE.2024.000052

• ELECTRONICS TECHNOLOGY • Previous Articles

Physical-layer secure hybrid task scheduling and resource management for fog computing IoT networks

Shibo ZHANG(), Hongyuan GAO(), Yumeng SU(), Rongchen SUN()

College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China

Received:2023-06-03 Online:2025-10-18 Published:2025-10-24
Contact: Hongyuan GAO E-mail:liangziyanhua@126.com;gaohongyuan@hrbeu.edu.cn;suyumeng1994@126.com;rongchensun@hrbeu.edu.cn
About author:
ZHANG Shibo was born in 1994. He received his B.S. degree in electronic and information engineering from Harbin Engineering University, Harbin, Heilongjiang, China, in 2016. He is currently working toward his Ph.D. degree with Harbin Engineering University. His research interests include fog/edge computing, cognitive relays, energy harvesting, heterogeneous networks, the Internet-of-Things, and future 6G networks. E-mail: liangziyanhua@126.com

GAO Hongyuan was born in 1977. He received his Ph.D. degree in communication and information systems, from the College of Information and Communication Engineering, Harbin Engineering University, China, in 2010. He was a visiting research professor with the Department of Computer and Information Science, Korea University, Sejong, South Korea, from 2015 to 2016. He is currently an associate professor with the College of Information and Communication Engineering, Harbin Engineering University. His current interests include wireless energy harvesting communications, intelligent computing, software radio, signal recognition and classification, cognitive radio, array signal processing, long term evolution-unlicensed, artificial intelligence, HetNets in 5G, communication theory and image processing, and massive multiple input multiple output. E-mail: gaohongyuan@hrbeu.edu.cn

SU Yumeng was born in 1994. She received her B.S. degree in electronic and information engineering from Harbin Engineering University, Harbin, Heilongjiang, China, in 2016. She is currently working toward her Ph.D. degree with Harbin Engineering University. Her current research interests include intelligent computing, resource management, secure communications, massive multiple input multiple output, co-frequency co-time full-duplex systems, network slicing, and beyond 5G technologies. E-mail: suyumeng1994@126.com

SUN Rongchen was born in 1988. He received his Ph.D. degree in communication and information systems, from the School of Electronic and Information Engineering, Beijing Jiaotong University, China, in 2018. He is currently an associate professor with the College of Information and Communication Engineering, Harbin Engineering University. His current interests include research on communication countermeasures, wireless channel modeling theory and key technologies. E-mail: rongchensun@hrbeu.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (61571149;62001139), the Initiation Fund for Postdoctoral Research in Heilongjiang Province (LBH-Q19098) and the Natural Science Foundation of Heilongjiang Province (LH2020F0178).

Abstract

Abstract:

Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks. Nevertheless, the fog computing Internet-of-Things (IoT) systems are susceptible to malicious eavesdropping attacks during the information transmission, and this issue has not been adequately addressed. In this paper, we propose a physical-layer secure fog computing IoT system model, which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers. The secrecy rate of the proposed model is analyzed, and the quantum galaxy–based search algorithm (QGSA) is proposed to solve the hybrid task scheduling and resource management problem of the network. The computational complexity and convergence of the proposed algorithm are analyzed. Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks. Moreover, the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios.

Key words: fog computing Internet-of-Things (IoT), physical layer security, hybrid task scheduling and resource management, quantum galaxy-based search algorithm (QGSA)

Shibo ZHANG, Hongyuan GAO, Yumeng SU, Rongchen SUN. Physical-layer secure hybrid task scheduling and resource management for fog computing IoT networks[J]. Journal of Systems Engineering and Electronics, 2025, 36(5): 1146-1160.

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Parameter	Value
Total number of FCSs	12
Task size for each IoT device in one time slot/(kbits)	[2,20]
Noise power density/(dBm/Hz)	−174
Total number of SRBs	10
Transmission power of each IoT device/dBm	40
SRB bandwidth/MHz	5
Total number of IoT devices	25
Maximum latency tolerance threshold of each IoT device/ms	[80, 400]
Total number of eavesdroppers	20
CPU processing rate of each FCS/(cycles/s)	[5,9]×10¹⁰
CPU cycles required for processing 1 bit data/(cycles/bit)	10⁴
Accusation delay/ms	5
Maximum number of CRBs	8
Pre-ratio $ \rho $	0.15
Chaotic sequence initial value	0.18
Control factor $ {\delta _1} $	0.3
Control factor $ {\delta _2} $	0.05×(1−$i/{i_{\max }}$)
Control factor $ {\delta _3} $	0.5
Control factor $ {\delta _4} $	0.15
Control factor $ {\delta _5} $	0.05
Swarm size	20
Selection threshold $ {\eta _1} $	0.4
Selection threshold $ {\eta _2} $	0.8
Maximum iteration number	1000

Physical-layer secure hybrid task scheduling and resource management for fog computing IoT networks

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