无人机群辅助边缘计算系统的任务卸载和资源分配联合优化

doi:10.12305/j.issn.1001-506X.2024.02.39

Abstract

Abstract:

To improve the performance of unmanned aerial vehicle swarm-assisted edge computing systems under load imbalancing scenarios, a new unmanned aerial vehicle swarm edge computing system is constructed to improve the utilization of computing resources by using offloading data among unmanned aerial vehicle. The weighted sum of the system's delay and energy consumption are minimized by jointly optimizing the offloading scheme, deployment, and resource allocation of multiple unmanned aerial vehicle. The problem is highly nonconvex, and a two-layer optimization scheme is proposed to solve the problem, i.e., the heuristic optimal evaluation algorithm. The upper layer uses a particle swarm algorithm to optimize the unmanned aerial vehicle locations. The lower layer uses a block coordinate descent algorithm to optimize the unmanned aerial vehicle data offloading and resource allocation under the determined locations. The simulation results show that the proposed scheme can effectively reduce the system cost and has obvious advantages over the benchmark strategies.

Key words: edge computing, unmanned aerial vehicle swarm, task offloading, resource allocation, location optimization

CLC Number:

TN925

Shihao LIU, Yangchao HUANG, Hang HU, Jiangbo SI, Huizhu HAN, Qi AN. Joint optimization of task offloading and resource allocation for UAV swarm-assisted edge computing systems[J]. Systems Engineering and Electronics, 2024, 46(2): 751-760.

Figures/Tables 12

Fig.1

Fig.2

Table 1

Fig.3

Fig.4

Table 2

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

References 34

1	LIU J , ZHOU A , LIU C H , et al. Reliability-enhanced task offloading in mobile edge computing environments[J]. IEEE Internet of Things Journal, 2022, 9 (13): 10382- 10396. doi: 10.1109/JIOT.2021.3115807
2	吴启晖, 王然, 黄振炎. 物联网的一种新范式: 智能频联网[J]. 物联网学报, 2018, 2 (1): 35- 41.
	WU Q H , WANG R , HUANG Z Y . A new paradigm of Internet of things: intelligent frequency networking[J]. Chinese Journal on Internet of Things, 2018, 2 (1): 35- 41.
3	LYU X C , NI W , TIAN H , et al. Optimal schedule of mobile edge computing for Internet of things using partial information[J]. IEEE Journal on Selected Areas in Communications, 2017, 35 (11): 2606- 2615. doi: 10.1109/JSAC.2017.2760186
4	张海君, 张资政, 隆克平. 基于移动边缘计算的NOMA异构网络资源分配[J]. 通信学报, 2020, 41 (4): 27- 33.
	ZHANG H J , ZHANG Z Z , LONG K P . Resource allocation in NOMA heterogeneous network based on MEC[J]. Journal on Communications, 2020, 41 (4): 27- 33.
5	ZENG Y , ZHANG R , LIM T J , et al. Wireless communications with unmanned aerial vehicles: opportunities and challenges[J]. IEEE Communications Magazine, 2016, 54 (5): 36- 42. doi: 10.1109/MCOM.2016.7470933
6	HOSSEIN M , TALEB T , AROUK O , et al. Low-altitude unmanned aerial vehicles-based Internet of Things services: comprehensive survey and future perspectives[J]. IEEE Internet of Things Journal, 2016, 3 (6): 899- 922. doi: 10.1109/JIOT.2016.2612119
7	LUO C, NIGHTINGALE J, ASEMOTA E, et al. A UAV-cloud system for disaster sensing applications[C]//Proc. of the IEEE 81st Vehicular Technology Conference, 2015.
8	WAN S , LU J X , FAN P Y , et al. To smart city: public safety network design for emergency[J]. IEEE Access, 2018, 6, 1451- 1460. doi: 10.1109/ACCESS.2017.2779137
9	LUO Y Z , DING W R , ZHANG B C , et al. Optimization of task scheduling and dynamic service strategy for multi-UAV-enabled mobile-edge computing system[J]. IEEE Trans. on Cognitive Communications and Networking, 2021, 7 (3): 970- 984. doi: 10.1109/TCCN.2021.3051947
10	吴启晖, 吴伟. 无人机辅助边缘计算的能量效率最大化算法设计[J]. 通信学报, 2020, 41 (10): 15- 24.
	WU Q H , WU W . Algorithm design on energy efficiency maximization for UAV-assisted edge computing[J]. Journal on Communi Cations, 2020, 41 (10): 15- 24.
11	张广驰, 陈娇, 崔苗, 等. 无人机交替中继通信及其轨迹优化和功率分配研究[J]. 电子与信息学报, 2021, 43 (12): 3554- 3562. doi: 10.11999/JEIT200684
	ZHANG G C , CHEN J , CUI M , et al. Trajectory optimization and power allocation for UAV alternate relay communications[J]. Journal of Electronics & Information Technology, 2021, 43 (12): 3554- 3562. doi: 10.11999/JEIT200684
12	COSTANZO F, LORENZO P D, BARBAROSSA S, et al. Dynamic resource optimization and altitude selection in UAV-based multi-access edge computing[C]//Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2020: 4985-4989.
13	LU H D , HE X M , DU M , et al. Edge QoE: computation offloading with deep reinforcement learning for internet of things[J]. IEEE Internet of Things Journal, 2020, 7 (10): 9255- 9265. doi: 10.1109/JIOT.2020.2981557
14	YANG L , YAO H P , WANG J L , et al. Multi-UAV-enabled load-balance mobile-edge computing for IoT networks[J]. IEEE Internet of Things Journal, 2020, 7 (8): 6898- 6908. doi: 10.1109/JIOT.2020.2971645
15	LYU J B , ZENG Y , ZHANG R , et al. Placement optimization of UAV-mounted mobile base stations[J]. IEEE Communications Letters, 2017, 21 (3): 604- 607. doi: 10.1109/LCOMM.2016.2633248
16	MOZAFFARI M , SAAD W , BENNIS M , et al. Efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage[J]. IEEE Communications Letters, 2016, 20 (8): 3984- 3997.
17	WANG Y , RU Z Y , WANG K Z , et al. Joint deployment and task scheduling optimization for large-scale mobile users in multi-UAV-enabled mobile edge computing[J]. IEEE Trans. on Cybernetics, 2020, 50 (9): 3984- 3997. doi: 10.1109/TCYB.2019.2935466
18	LUO Y Z , DING W R , ZHANG B C , et al. Optimization of task scheduling and dynamic service strategy for multi-UAV-enabled mobile-edge computing system[J]. IEEE Trans. on Cognitive Communications and Networking, 2021, 7 (3): 970- 984. doi: 10.1109/TCCN.2021.3051947
19	YANG Z H , PAN C H , WANG K Z , et al. Energy efficient resource allocation in UAV-enabled mobile edge computing networks[J]. IEEE Trans. on Wireless Communications, 2019, 18 (9): 4576- 4589. doi: 10.1109/TWC.2019.2927313
20	HUANG W F, GUO H Z, LIU J J, et al. Task offloading in UAV swarm-based edge computing: grouping and role division[C]//Proc. of the IEEE Global Communications Conference, 2021.
21	DIAO X B , WANG M , ZHENG J C , et al. Fairness-aware offloading and trajectory optimization for multi-UAV enabled multi-access edge computing[J]. IEEE Access, 2020, 8, 124359- 124370. doi: 10.1109/ACCESS.2020.3006112
22	YU Z , GONG Y L . Joint differential evolution and successive convex approximation in UAV-enabled mobile edge computing[J]. IEEE Access, 2022, 10, 57413- 57426. doi: 10.1109/ACCESS.2022.3176362
23	嵇介曲, 朱琨, 易畅言, 等. 多无人机辅助移动边缘计算中的任务卸载和轨迹优化[J]. 物联网学报, 2021, 5 (1): 27- 35.
	JI J Q , ZHU K , YI C Y , et al. Joint task offloading and trajectory optimization for multi-UAV assisted mobile edge computing[J]. Chinese Journal on Internet of Things, 2021, 5 (1): 27- 35.
24	ZHANG Q X , CHEN J G , JI L , et al. Response delay optimization in mobile edge computing enabled UAV swarm[J]. IEEE Trans. on Vehicular Technology, 2020, 69 (3): 3280- 3295. doi: 10.1109/TVT.2020.2964821
25	WANG J J , JIANG C X , HAN Z , et al. Taking drones to the next level: cooperative distributed unmanned aerial-vehicular networks for small and mini-drones[J]. IEEE Vehicular Technology Magazine, 2017, 12 (3): 73- 82. doi: 10.1109/MVT.2016.2645481
26	ZHU S C , GUI L , CHENG N , et al. UAV-enabled computation migration for complex missions: a reinforcement learning approach[J]. IET Communications, 2020, 14 (5): 2472- 2480.
27	LIU B C , ZHANG W K , CHEN W H , et al. Online computation offloading and traffic routing for uav swarms in edge-cloud computing[J]. IEEE Trans. on Vehicular Technology, 2020, 69 (8): 8777- 8791. doi: 10.1109/TVT.2020.2994541
28	WU W , ZHOU F H , WANG B Y , et al. Unmanned aerial vehicle swarm-enabled edge computing: potentials, promising technologies, and challenges[J]. IEEE Wireless Communications, 2022, 29 (4): 78- 85. doi: 10.1109/MWC.103.2100286
29	CHEN J G, ZHANG Q X, FENG Z Y. Timeliness analysis of service-driven collaborative mobile edge computing in UAV swarm[C]//Proc. of the IEEE Globecom Workshops, 2019.
30	FARACI G , GRASSO C , SCHEMBRA G . Design of a 5G network slice extension with MEC UAVs managed with reinforcement learning[J]. IEEE Journal on Selected Areas in Communications, 2020, 38 (10): 2356- 2371. doi: 10.1109/JSAC.2020.3000416
31	YUAN W , NAHRSTEDT K . Energy-efficient soft real-time CPU scheduling for mobile multimedia systems[J]. ACM Trans. on Computer Systems, 2006, 24 (3): 292- 331. doi: 10.1145/1151690.1151693
32	YU Z , GONG Y M , GUO S M . Joint task offloading and resource allocation in UAV-enabled mobile edge computing[J]. IEEE Internet of Things Journal, 2020, 7 (4): 3147- 3159. doi: 10.1109/JIOT.2020.2965898
33	SHI Y, EBERHART R. A modified particle swarm optimizer[C]//Proc. of the IEEE International Conference on Evolutionary Computation Proceedings, 1998: 69-73.
34	KATWE M , SINGH K , SHARMA P , et al. Energy efficiency maximization for UAV-assisted full-Duplex NOMA system: user clustering and resource allocation[J]. IEEE Trans. on Green Communications and Networking, 2022, 6 (2): 992- 1008. doi: 10.1109/TGCN.2021.3134642

参数	取值	参数	取值
H/m	100	p_i^u/W	0.1
α₀/dBm	-90	C	100
K^[31]	10^－28	B_u/MHz	0.5
p^u/W	0.1	B_i/MHz	0.5
ρ	5	R	4

优化后的无人机位置	系统成本	随机分布的无人机位置/m	系统成本	节省成本/%
(907.9, 898.7, 100)m, (1 361.8, 707.5, 100)m(361.5, 1681.9, 100)m, (1 228.5, 1 541.1, 100)m	201.8	(22, 510, 100), (1 380, 58, 100), (622, 1 154, 100), (1 079, 1 217, 100)	231.9	13.0
		(340, 381, 100), (1 981, 3, 100), (949, 1 558, 100), (1 403, 1 875, 100)	232.8	13.3
		(0, 0, 100), (1 000, 0, 100), (0, 2 000, 100), (2 000, 2 000, 100)	236.2	14.6
		(0, 0, 100), (2 000, 0, 100), (0, 2 000, 100), (2 000, 2 000, 100)	240.7	16.2
		(776, 147, 100), (1 775, 277, 100), (363, 1 864, 100), (1 684, 1 066, 100)	234.1	13.8

[1]	Yuting ZHANG, Jingyu YANG. Capability-based defense resource allocation method [J]. Systems Engineering and Electronics, 2024, 46(2): 599-604.
[2]	Dejiang LU, Xing WANG, You CHEN, Xing HU. Adaptive scheduling method of joint multi-resource for cooperative interference of networked radar system [J]. Systems Engineering and Electronics, 2023, 45(9): 2744-2754.
[3]	Bingxue ZHANG, Xisheng LI, Jia YOU, Weiren SONG. End-edge collaborative network generation algorithm based on node composite characteristics [J]. Systems Engineering and Electronics, 2023, 45(8): 2588-2596.
[4]	Yaohua XU, Huiping WANG, Guizhu WANG, Chenglong ZHU, Mengqin DING, Fang JIANG, Yi WANG. Resource allocation algorithm for internet of vehicles based on graph coloring and three-dimensional matching [J]. Systems Engineering and Electronics, 2023, 45(3): 869-875.
[5]	Han CHEN, Jing ZHANG, Jun DONG, Jie DONG. MEC offloading scheme based on joint optimization of subtaskscheduling and delay [J]. Systems Engineering and Electronics, 2023, 45(2): 572-579.
[6]	Bozhi DONG, Jiang ZHU, Haibo ZHANG. SCMA-based energy efficiency resource allocation scheme in amplify-forward relay system [J]. Systems Engineering and Electronics, 2022, 44(6): 2035-2042.
[7]	Hong ZOU, Chenyang BAI, Peng HE, Yaping CUI, Ruyan WANG, Dapeng WU. Edge service placement strategy based on distributed deep learning [J]. Systems Engineering and Electronics, 2022, 44(5): 1728-1737.
[8]	Yuanyuan ZHANG, Yang GAO, Peng ZHU, Jintao LIU, Shushan GU. UAV reconnaissance tactical planning based on colored Petri nets [J]. Systems Engineering and Electronics, 2022, 44(3): 900-907.
[9]	Shanxue CHEN, Shengjin WU, Bowen GU. Energy efficiency optimization algorithm for uplink NOMA systems with time reversal [J]. Systems Engineering and Electronics, 2022, 44(3): 1007-1013.
[10]	Xueyong YU, Ye ZHU, Lixiang QIU, Hongbo ZHU. Energy efficient offloading strategy for UAV aided edgecomputing systems [J]. Systems Engineering and Electronics, 2022, 44(3): 1022-1029.
[11]	Zhigang JIN, Chenxu DUAN, Qiuling YANG, Yishan SU. A new mechanism for reef coral monitoring based on underwater cloud-edge collaborative architecture [J]. Systems Engineering and Electronics, 2022, 44(12): 3829-3836.
[12]	Yuzhi ZHANG, Yanjing SUN, Bin WANG, Yang LIU. Underwater acoustic adaptive OFDMA based on feedback channel state information [J]. Systems Engineering and Electronics, 2021, 43(8): 2321-2331.
[13]	Zhenzhen YAN, Bo LI, Mao YANG, Zhongjiang YAN. Hybrid non-orthogonal multiple access method based on genetic algorithm [J]. Systems Engineering and Electronics, 2021, 43(3): 832-838.
[14]	Fatang CHEN, Zhihao ZHANG, Hebin LI, Zhiqiang MEI. Fairness resource allocation algorithm based on OFDMA scheduling access in 802.11ax system [J]. Systems Engineering and Electronics, 2021, 43(11): 3352-3359.
[15]	Chunqi JIANG, Na'e ZHENG, Zong ZUO, Sheng WANG, Xiang CHEN. Antenna selection of distributed MIMO radar on target tracking with key target highlighted [J]. Systems Engineering and Electronics, 2021, 43(10): 2860-2868.

Joint optimization of task offloading and resource allocation for UAV swarm-assisted edge computing systems

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 12

References 34

Related Articles 15

Recommended Articles

Metrics

Comments