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1. 西安电子科技大学 计算机科学与技术学院,陕西 西安 710071
2. 陕西省智能人机交互与可穿戴技术重点实验室,陕西 西安 710071
[ "张超(2000—),男,西安电子科技大学硕士研究生,E-mail:[email protected]" ]
[ "赵辉(1983—),男,副教授,博士,E-mail:[email protected]" ]
[ "张智峰(1998—),男,西安电子科技大学硕士研究生,E-mail:[email protected]" ]
王静(1981—),女,副教授,博士,E-mail:[email protected]
[ "万波(1976—),男,教授,博士,E-mail:[email protected]" ]
[ "王泉(1970—),男,教授,博士,E-mail:[email protected]" ]
纸质出版日期:2024-08-20,
网络出版日期:2024-04-07,
收稿日期:2023-09-28,
移动端阅览
张超, 赵辉, 张智峰, 等. 边缘协作环境下最小化完工时间任务调度方法[J]. 西安电子科技大学学报, 2024,51(4):114-127.
Chao ZHANG, Hui ZHAO, Zhifeng ZHANG, et al. Task scheduling method for minimizing completion time in edge collaborative environment. [J]. Journal of Xidian University, 2024,51(4):114-127.
张超, 赵辉, 张智峰, 等. 边缘协作环境下最小化完工时间任务调度方法[J]. 西安电子科技大学学报, 2024,51(4):114-127. DOI: 10.19665/j.issn1001-2400.20240308.
Chao ZHANG, Hui ZHAO, Zhifeng ZHANG, et al. Task scheduling method for minimizing completion time in edge collaborative environment. [J]. Journal of Xidian University, 2024,51(4):114-127. DOI: 10.19665/j.issn1001-2400.20240308.
由于用户地理位置分布不均可能导致边缘服务器负载不均衡
难以为用户提供满意的服务质量。此外
边缘服务器可用资源有限
一些大任务可能难以全部卸载到边缘服务器。针对以上问题
利用多个边缘服务器之间的协作
结合任务部分卸载方式
提出一种边缘协作环境下最小化完工时间的任务调度方法。首先
结合边缘水平协作和任务部分卸载技术
考虑多用户多边缘服务器场景下用户和边缘服务器的位置关系
以最小化任务完工时间为目标
建立任务部分卸载调度模型;其次
提出基于改进分组教学优化算法的任务调度算法
联合优化边缘服务器计算资源分配、用户-边缘服务器关联决策、任务卸载比例以及执行位置决策
以最小化任务完工时间为目标
实现边缘计算环境下任务的高效调度;最后
通过实验将提出的任务调度算法与其他算法在多个指标下进行对比。实验结果表明
所提方法能够有效降低任务完工时间。
The uneven geographical distribution of users may lead to unbalanced load on edge servers
which makes it difficult to provide satisfactory service quality for users.In addition
the available resources of the edge server are limited
and some large tasks may be difficult to offload to the edge server.To solve the above problems
this paper proposes a task scheduling method to minimize the completion time in the edge collaboration environment by utilizing the collaboration among multiple edge servers and combining the task partial offloading technology.First
by combining the edge of horizontal collaboration and task partial offloading technology and considering the position relationship between users and edge servers in multi-user multi-edge server scenario
a task partial offloading and scheduling model is established to minimize the task completion time.Second
a task scheduling algorithm based on the Improved Group Teaching Optimization Algorithm(IGTOA) is proposed to jointly optimize the edge server computing resource allocation
user-edge server association decision
task offloading ratio and execution location decision.With minimizing the task completion time as the goal
efficient task scheduling is achieved under edge computing environment.Finally
the proposed task scheduling algorithm is compared with DTOSO
HJTORA and ACS algorithms under multiple indexes.Experimental results show that the proposed method can effectively reduce the task completion time.
边缘协作部分卸载调度算法分组教学优化算法
edge collaborationpartial offloadingscheduling algorithmgroup teaching optimization algorithm
LIANG Y, WANG W, ZHENG X, et al. Collaborative Edge Service Placement for Maximizing QoS with Distributed Data Cleaning[C]//2023 IEEE/ACM 31st International Symposium on Quality of Service(IWQoS).Piscataway:IEEE, 2023: 1-4.
宋宇波, 金星妤, 燕锋, 等. 车联网中移动边缘计算的安全高效节能卸载策略[J]. 清华大学学报(自然科学版), 2021, 61(11):1246-1253.
SONG Yubo, JING Xingyu, YAN Feng, et al. Secure and Energy Efficient Offloading of Mobile Edge Computing in the Internet of Vehicles[J]. Journal of Tsinghua University(Science and Technology), 2021, 61(11):1246-1253.
YUAN H, ZHOU M C. Profit-Maximized Collaborative Computation Offloading and Resource Allocation in Distributed Cloud and Edge Computing Systems[J]. IEEE Transactions on Automation Science and Engineering, 2020, 18(3):1277-1287.
DING Y, LI K, LIU C, et al. A Potential Game Theoretic Approach to Computation Offloading Strategy Optimization in End-Edge-Cloud Computing[J]. IEEE Transactions on Parallel and Distributed Systems, 2021, 33(6):1503-1519.
ZHOU T, YUE Y, QIN D, et al. Joint Device Association,Resource Allocation,and Computation Offloading in Ultradense Multidevice and Multitask IoT Networks[J]. IEEE Internet of Things Journal, 2022, 9(19):18695-18709.
赵辉, 冯南之, 王泉, 等. 面向边缘计算平台的半线上任务动态调度方法[J]. 西安电子科技大学学报, 2021, 48(6):8-15.
ZHAO Hui, FENG Nanzhi, WANG Quan, et al. Dynamic Semi-Online Task Scheduling Method for the Edge Computing Platform[J]. Journal of Xidian University, 2021, 48(6):8-15.
彭青蓝, 夏云霓, 郑万波, 等. 一种去中心化的在线边缘任务调度与资源分配方法[J]. 计算机学报, 2022, 45(7):1462-1477.
PENG Qinglan, XIA Yunni, ZHENG Wanbo, et al. A Decentralized Approach to Online Edge Task Scheduling and Resource Allocation[J]. Journal of Computer Science, 2022, 45(7):1462-1477.
WANG K, CHEN W, LI J, et al. Joint Task Offloading and Caching for Massive MIMO-Aided Multi-Tier Computing Networks[J]. IEEE Transactions on Communications, 2022, 70(3):1820-1833.
邝祝芳, 陈清林, 李林峰, 等. 基于深度强化学习的多用户边缘计算任务卸载调度与资源分配算法[J]. 计算机学报, 2022, 45(4):812-824.
KUANG Zhufang, CHEN Qinglin, LI Linfeng, et al. Task Offloading Scheduling and Resource Allocation Algorithm for Multi-User Edge Computing Based on Deep Reinforcement Learning[J]. Journal of Computer Science, 2022, 45(4):812-824.
NING Z, DONG P, WANG X, et al. Partial Computation Offloading and Adaptive Task Scheduling for 5G-Enabled Vehicular Networks[J]. IEEE Transactions on Mobile Computing, 2020, 21(4):1319-1333.
MALIK R, VU M. On-Request Wireless Charging and Partial Computation Offloading in Multi-Access Edge Computing Systems[J]. IEEE Transactions on Wireless Communications, 2021, 20(10):6665-6679.
ZHANG W, ZHANG Z, ZEADALLY S, et al. Energy-Efficient Workload Allocation and Computation Resource Configuration in Distributed Cloud/Edge Computing Systems with Stochastic Workloads[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(6):1118-1132.
HU S, LI G. Dynamic Request Scheduling Optimization in Mobile Edge Computing for IoT Applications[J]. IEEE Internet of Things Journal, 2020, 7(2):1426-1437.
ELGENDY I A, ZHANG W Z, HE H, et al. Joint Computation Offloading and Task Caching for Multi-User and Multi-Task MEC Systems:Reinforcement Learning-Based Algorithms[J]. Wireless Networks, 2021, 27(3):2023-2038.
LIU X, YU J, WANG J, et al. Resource Allocation with Edge Computing in IoT Networks via Machine Learning[J]. IEEE Internet of Things Journal, 2020, 7(4):3415-3426.
LIU X, ZHAO X, LIU G, et al. Collaborative Task Offloading and Service Caching Strategy for Mobile Edge Computing[J]. Sensors, 2022, 22(18):6760.
RAO H, JIA H, WU D, et al. A Modified Group Teaching Optimization Algorithm for Solving Constrained Engineering Optimization Problems[J]. Mathematics, 2022, 10(20):3765.
ZHANG Y, JIN Z. Group Teaching Optimization Algorithm:A Novel Metaheuristic Method for Solving Global Optimization Problems[J]. Expert Systems with Applications, 2020,148:113246-113264.
GUO F, ZHANG H, JI H, et al. An Efficient Computation Offloading Management Scheme in the Densely Deployed Small Cell Networks with Mobile Edge Computing[J]. IEEE/ACM Transactions on Networking, 2018, 26(6):2651-2664.
MAHMOOD A, HONG Y, EHSAN M K, et al. Optimal Resource Allocation and Task Segmentation in IoT Enabled Mobile Edge Cloud[J]. IEEE Transactions on Vehicular Technology, 2021, 70(12):13294-13303.
LIU Z, FAN J, GENG S, et al. Joint Optimization of Task Offloading and Computing Resource Allocation in MEC-D2D Network[C]//2022 IEEE 5th International Conference on Computer and Communication Engineering Technology(CCET).Piscataway:IEEE, 2022: 256-260.
TRAN T X, POMPILI D. Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks[J]. IEEE Transactions on Vehicular Technology, 2018, 68(1):856-868.
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