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A Task Offloading Algorithm using Multi-Objective Optimization under Hybrid Mode in Mobile Edge Computing

delete2023-11-30
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PRE
AI
H
Haole Hou
Z
Zheng-Yi Chai *
X
Xu Liu
Y
Yalun Li
Y
Yue Zeng
DOI:10.1007/s11036-023-02272-xdelete
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Abstract

Abstract

En 中文
In mobile edge computing (MEC), edge clients have the capability to offload their computing tasks to edge servers or other edge clients, aiming to reduce their energy consumption and latency. However, the process of offloading introduces additional energy consumption and time due to long-distance network transmission, which presents a significant challenge in jointly minimizing energy consumption and latency for edge clients. To address this challenge, we formulate the problem as a constrained multi-objective optimization problem and propose an enhanced multi-objective evolutionary algorithm, named MOEA-TOMEC, to determine optimal task offloading strategies in MEC. The proposed algorithm aims to minimize both the extra energy consumption and latency. To overcome the limitations of a single offloading mode in complex network environments, we introduce a hybrid offloading mode within our algorithm. This hybrid approach combines partial offloading and full offloading to achieve lower energy consumption and latency. Additionally, we propose a device classification algorithm that plays a crucial role in initializing the population. This algorithm incorporates low-battery devices as relays in the offloading decisions, thereby enhancing population diversity. By generating a superior initial population and expanding the breadth of the learning space, our proposed algorithm achieves improved performance. Experimental results demonstrate the effectiveness of our proposed algorithm. In comparison to existing algorithms, our approach reduces the energy consumption and latency of edge clients by an average of 9.13% and 13.91%, respectively.
Keywords:
Mobile edge computing
Multi-objective optimization
Evolutionary algorithms
Energy consumption
Delay

Journal

Mobile Networks and Applications cover
Mobile Networks and Applications
IF:
2
Papers:
83
Citations:
3.3K

Organization

J
Jinling Institute of Technology
Scholars:
1.2K
Papers: 971
Citations: 1.3K
T
Tiangong University
Scholars:
1.2W
Papers: 7.7K
Citations: 1.1W
Cited Papers

Cited Papers

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Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
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Mobile Edge Computing: A Survey
err2018-02-01
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errAbbas, Nasir; Zhang, Yan; Taherkordi, Amir; Skeie, Tor
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Computation offloading in mobile edge computing networks: A survey
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errFeng, Chuan; Han, Pengchao; Zhang, Xu; Yang, Bowen; Liu, Yejun; Guo, Lei
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A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks
err2017-01-01
err446
PREAI
errYetgin, Halil; Cheung, Kent Tsz Kan; El-Hajjar, Mohammed; Hanzo, Lajos
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Price and Risk Awareness for Data Offloading Decision-Making in Edge Computing Systems
err2022-12-01
err91
errOAAI
errMitsis, Giorgos; Tsiropoulou, Eirini Eleni; Papavassiliou, Symeon
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