Energy-Efficient and Latency-Optimized Computation Offloading with Improved MOEA for Industrial Internet of Things
Document Type
Conference Proceeding
Publication Date
1-1-2024
Abstract
The unprecedented prosperity of the industrial Internet of Things has thoroughly facilitated the transition from traditional manufacturing towards intelligent manufacturing. In industrial environments, resource-constrained industrial equipments (IEs) often fail to meet the diverse demands of numerous compute-intensive and latency-sensitive tasks. Mobile edge computing has emerged as an innovative paradigm for lower latency and energy consumption for IEs. However, computational offloading and coordinating of multiple IEs with diverse task types and multiple edge nodes in industrial environments poses challenges. To address this challenge, we propose a multi-task approach encompassing scientific and concurrent workflow tasks to achieve energy-efficient and latency-optimized computation offloading. Furthermore, this work designs an improved Quantum Multi-objective Grey wolf optimizer with Manta ray foraging and Associative learning (QMGMA) to optimize multi-task computation offloading. Comprehensive experiments demonstrate the superior efficiency and stability of QMAGA compared to state-of-the-art algorithms in balancing latency and energy consumption. QMAGA improves average inverse generation distance and average spacing by 37% and 31% on average than multi-objective grey wolf optimizer, non-dominated sorting genetic algorithm II, and multi-objective multi-verse optimization, proving the convergence and diversity of its non-dominated solutions.
Identifier
85217874974 (Scopus)
ISBN
[9781665410205]
Publication Title
Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
External Full Text Location
https://doi.org/10.1109/SMC54092.2024.10831388
ISSN
1062922X
First Page
852
Last Page
857
Grant
62173013
Fund Ref
China Scholarship Council
Recommended Citation
Zhai, Jiahui; Bi, Jing; Yuan, Haitao; Yang, Jinhong; Zhang, Jia; and Zhou, Meng Chu, "Energy-Efficient and Latency-Optimized Computation Offloading with Improved MOEA for Industrial Internet of Things" (2024). Faculty Publications. 708.
https://digitalcommons.njit.edu/fac_pubs/708
