基于不确定联盟博弈的EIP收益预估策略研究

赵庶旭; 夏心雨; 王小龙

doi:10.11959/j.issn.1000-436x.2024220

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基于不确定联盟博弈的EIP收益预估策略研究

学术论文 | 更新时间：2025-01-14

- 基于不确定联盟博弈的EIP收益预估策略研究
- Uncertain edge coalition game based EIP revenue estimation strategy
- 通信学报 2024年45卷第12期页码：111-123
- 作者机构：
  
  兰州交通大学电子与信息工程学院，甘肃兰州 730070
- 作者简介：
  
  [ "赵庶旭（1976- ），男，山东青岛人，博士，兰州交通大学教授，主要研究方向为智能交通、边缘计算等。" ]
  [ "夏心雨（1997- ），女，黑龙江大庆人，兰州交通大学硕士生，主要研究方向为边缘计算、边缘联盟等。" ]
  [ "王小龙（1989- ），男，甘肃定西人，博士，兰州交通大学讲师，主要研究方向为边缘计算、边缘联盟等。" ]
- 基金信息：
  
  甘肃省重点研发计划基金资助项目(20YF8GA123);甘肃省高校教师创新基金资助项目(2024B-059);兰州交通大学青年科学基金资助项目(1200061307)
- DOI：10.11959/j.issn.1000-436x.2024220
  中图分类号： TN92
- 收稿：2024-09-02，
  
  修回：2024-12-19，
  
  纸质出版：2024-12-25
- 稿件说明：
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赵庶旭,夏心雨,王小龙.基于不确定联盟博弈的EIP收益预估策略研究[J].通信学报,2024,45(12):111-123.

ZHAO Shuxu,XIA Xinyu,WANG Xiaolong.Uncertain edge coalition game based EIP revenue estimation strategy[J].Journal on Communications,2024,45(12):111-123.
赵庶旭,夏心雨,王小龙.基于不确定联盟博弈的EIP收益预估策略研究[J].通信学报,2024,45(12):111-123. DOI： 10.11959/j.issn.1000-436x.2024220.

ZHAO Shuxu,XIA Xinyu,WANG Xiaolong.Uncertain edge coalition game based EIP revenue estimation strategy[J].Journal on Communications,2024,45(12):111-123. DOI： 10.11959/j.issn.1000-436x.2024220.

摘要

边缘计算环境中存在通信信道风险和边缘服务器故障等风险因素，会导致处理任务所需的计算资源与边缘联盟分配的资源产生失配问题，对此，提出了一种基于不确定联盟结构博弈的边缘联盟及其成员边缘基础设施供应商（EIP）的收益预估方法。首先通过混合整数线性规划方法构建资源调度模型以最大化边缘联盟收益。其次引入信念结构对联盟收益进行高、中、低和未知4种情况的概率进行表征。最后利用不确定Owen值提前一个时隙对联盟中EIP进行区间收益预估。仿真结果表明，所提预估方法在通信信道风险以及服务器故障2种风险下的准确率分别为91.25%、82.5%，平均准确率为86.88%，且在考虑周期性任务到达的情况下，实现了对EIP收益区间的准确预估。

Abstract

In the edge computing environment

there are risks such as communication channel risks and edge server failures

which can lead to a mismatch between the computing resources required for task processing and the resources allocated by the edge coalition. In response

a revenue forecasting method for the edge coalition and its member edge infrastructure provider (EIP) based on the game theory of uncertain coalition structures was proposed. Firstly

a resource scheduling model was constructed using a mixed integer linear programming method to maximize the revenue of the edge coalition. Secondly

a belief structure was introduced to characterize the probabilities of high

medium

low

and unknown scenarios for the coalition's revenue. Finally

the uncertain Owen value was used to estimate the interval revenue of the EIP in the coalition one time slot in advance. The simulation results show that the accuracy of this forecasting method under the two risks of channel risk and server failure is 91.25% and 82.5% respectively

with an average accuracy of 86.88%

achieving a relatively accurate forecast of the EIP’ revenue.

关键词

Keywords

references

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