Cooperative Computation Offloading and Resource Management Based on Improved Genetic Algorithm in NOMA-MEC Systems

ZHOU Tianqing; HU Haiqin; ZENG Xinliang

doi:10.11999/JEIT220306

Volume 44 Issue 9

Sep. 2022

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ZHOU Tianqing, HU Haiqin, ZENG Xinliang. Cooperative Computation Offloading and Resource Management Based on Improved Genetic Algorithm in NOMA-MEC Systems[J]. Journal of Electronics & Information Technology, 2022, 44(9): 3014-3023. doi: 10.11999/JEIT220306

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ZHOU Tianqing, HU Haiqin, ZENG Xinliang. Cooperative Computation Offloading and Resource Management Based on Improved Genetic Algorithm in NOMA-MEC Systems[J]. Journal of Electronics & Information Technology, 2022, 44(9): 3014-3023. doi: 10.11999/JEIT220306

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Cooperative Computation Offloading and Resource Management Based on Improved Genetic Algorithm in NOMA-MEC Systems

doi: 10.11999/JEIT220306

School of Information Engineering, East China Jiaotong University, Nanchang 330013, China

Funds: The National Natural Science Foundation of China (61861017, 61861018, 61961020, 62171119), The National Key Research and Development Program of China (2020YFB1807201)

Received Date: 2022-03-22
Accepted Date: 2022-08-09
Rev Recd Date: 2022-08-08

Available Online: 2022-08-12

Publish Date: 2022-09-19

Abstract

Abstract

To balance the network loads and utilize fully the network resources, joint cooperative computation offloading and wireless resource management is considered for ultra-dense heterogeneous edge computing networks with multiple users and multiple tasks, which minimizes the system energy consumption under the constraints of users’ delay. During the problem modeling, a frequency spectrum partitioning mechanism is introduced to tackle serious network interference caused by ultra-dense deployment of base stations, and Non-Orthogonal Multiple Access (NOMA) technology is introduced to improve the uplink frequency spectrum efficiency. Considering that the optimization problem is a nonlinear mixed-integer form, according to Adaptive Genetic Algorithm with Diversity-Guided Mutation (AGADGM), an effective algorithm used for cooperative computation offloading and resource allocation is designed. The simulation results show that proposed algorithm could achieve lower system energy consumption than other existing algorithms under strict constraints of users’ delay.

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References(19)

References

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