Resource-sharing allocation method based on dwarf mongoose optimization algorithm in vehicle computing

LIU Xi; LIU Jun; WU Hong; LI Weidong

doi:10.11959/j.issn.2096-3750.2024.00444

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Resource-sharing allocation method based on dwarf mongoose optimization algorithm in vehicle computing

Topic: Computing Power Internet of Things | 更新时间：2025-01-20

- Resource-sharing allocation method based on dwarf mongoose optimization algorithm in vehicle computing
- Chinese Journal on Internet of Things Vol. 8, Issue 4, Pages: 89-97(2024)
- 作者机构：
  
  1.曲靖师范学院信息工程学院，云南曲靖 655011
  2.云南经济管理学院教育学院，云南昆明 650106
  3.云南大学数学与统计学院，云南昆明 650500
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62462056)
- DOI：10.11959/j.issn.2096-3750.2024.00444
  CLC：
- Received：15 October 2024，
  
  Revised：2024-11-29，
  
  Published：10 December 2024
- 稿件说明：
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刘曦,刘俊,吴鸿等.车计算中基于侏儒猫鼬优化算法的资源共享分配方法[J].物联网学报,2024,08(04):89-97.

LIU Xi,LIU Jun,WU Hong,et al.Resource-sharing allocation method based on dwarf mongoose optimization algorithm in vehicle computing[J].Chinese Journal on Internet of Things,2024,08(04):89-97.
刘曦,刘俊,吴鸿等.车计算中基于侏儒猫鼬优化算法的资源共享分配方法[J].物联网学报,2024,08(04):89-97. DOI： 10.11959/j.issn.2096-3750.2024.00444.

LIU Xi,LIU Jun,WU Hong,et al.Resource-sharing allocation method based on dwarf mongoose optimization algorithm in vehicle computing[J].Chinese Journal on Internet of Things,2024,08(04):89-97. DOI： 10.11959/j.issn.2096-3750.2024.00444.

摘要

在车计算中，拥有强大计算能力和丰富传感设备的智能车为用户提供服务，其中众多的传感设备能为用户提供不限时间、地点的服务。智能车拥有大量计算资源和传感资源，其中计算资源为单个用户独享，而传感资源能被多个用户共享。针对车计算的特点，首先设计了一种基于资源共享的资源分配新模型，提出一种基于侏儒猫鼬优化算法的资源共享分配方法。然后针对资源分配的离散问题，提出一种不可行解的修正算法。最后为了解决侏儒猫鼬优化算法易于陷入局部最优解的问题，提出一种基于随机和贪心策略结合的初始解生成算法，以提高算法收敛速度，使其能够快速得到最优分配方案。实验结果表明，所提方法在不同的分配环境下均有较好的表现，并且有较强的适应能力。

Abstract

In vehicle computing

the intelligent vehicle which has strong computing capability and abundant sensing devices provides services for users. Many sensing devices can provide services for users without the limits of time and place. Intelligent vehicles have large amount computing and sensing resources

where computing resources are used individually by users while sensing resources can be shared by multiple users. According to the characteristics of intelligent vehicles

a new resource allocation model based on resource sharing was proposed. A resource sharing allocation method based on dwarf mongoose optimization was proposed. A repairing algorithm was proposed to transform infeasible solutions into feasible solutions. A new solution generation algorithm based on the random and greedy strategy was proposed to address the problem of the dwarf mongoose optimization algorithm being prone to getting stuck in local optima

to improve the convergence speed and obtain the optimal solution. The experimental results show that the proposed strategy performs well in different allocation environments and is adaptable.

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