计算机科学

计算机科学 ›› 2026, Vol. 53 ›› Issue (2): 379-386.doi: 10.11896/jsjkx.241100196

• 计算机网络 • 上一篇    下一篇

面向用户的移动群智感知动态负载均衡任务分配策略

李凡, 吴亚辉, 邓苏, 马武彬, 周浩浩   

  1. 国防科技大学信息系统工程重点实验室 长沙 410073
  • 收稿日期:2024-11-29 修回日期:2025-06-30 发布日期:2026-02-10
  • 通讯作者: 吴亚辉(wuyahui@nudt.edu.cn)
  • 作者简介:(lifan23@nudt.edu.cn)
  • 基金资助:
    国家自然科学基金面上项目(61871388)

Load Balancing Task Allocation Strategy for User-oriented Mobile Crowdsensing

LI Fan, WU Yahui, DENG Su, MA Wubin, ZHOU Haohao   

  1. National Key Laboratory of Information Systems Engineering,National University of Defense Technology,Changsha 410073,China
  • Received:2024-11-29 Revised:2025-06-30 Online:2026-02-10
  • About author:LI Fan,born in 2002,postgraduate.Her main research interests include mobile crowdsensing and optimization algorithm.
    WU Yahui,born in 1983,Ph.D,associate professor.His main research interests include Internet of Things,network optimization and data mining.
  • Supported by:
    General Program of National Natural Science Foundation of China(61871388).

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摘要： 移动群智感知系统中,用户的参与意愿和体验对系统的整体性能和长期持续运行具有重要影响。现有面向用户的任务分配策略大多只考虑到用户的成本效益,忽视了任务分配过程的负载均衡问题,致使部分关键节点因负载较重而过早退出,影响系统的长期效能。为此,构建了一种以用户为中心的长时域动态任务分配模型,针对模型的动态性和持续性的特点,提出了基于改进Lyapunov优化理论的求解算法,同步考虑了系统整体效益和负载均衡性的双重优化,实现动态环境下的带有负载均衡约束的任务最优的分配。实验结果表明,所提算法在保证队列稳定性和系统整体效益最优的前提下,将用户的负载均衡性提升了近20%。

关键词: 移动群智感知, 负载均衡, Lyapunov优化理论, 系统整体效益

Abstract: In mobile crowdsensing systems,the user’s participation intention and experience have an important impact on the overall performance and long-term sustainable operation of the system.Most existing user-oriented task allocation strategies only consider the cost-benefits of users and ignore the load balancing issue in the task allocation process,resulting in the premature exit of some key nodes due to heavy loads,which affects the long-term performance of the system.Therefore,this paper proposes a user-centered,long-time dynamic task allocation model.Aiming at the dynamics and persistence of the model,a solution algorithm based on improved Lyapunov optimization theory is proposed,which simultaneously considers the dual optimization of overall system benefits and load balancing,achieving optimal task allocation with load balancing constraints in dynamic environments.Experimental results demonstrate that the proposed algorithm improves the load balancing of users by nearly 20% under the pre-mise of ensuring queue stability and optimal overall system benefits.

Key words: Mobile crowdsensing, Load balancing, Lyapunov optimization theory, Overall system benefits

中图分类号: 

  • TP301
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