A cooperative failure detector in vehicular cloud computing

LIU Jiaxi; DONG Jian; WU Zhibo; WU Jin; WEN Dongxin; ZHAO Yao

doi:10.11918/j.issn.0367-6234.201708010

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A cooperative failure detector in vehicular cloud computing

更新时间：2026-10-19

- A cooperative failure detector in vehicular cloud computing
- Vol. 50, Issue 5, Pages: 24-29(2018)
- 作者机构：
  
  哈尔滨工业大学容错与移动计算中心,哈尔滨,150001
- 作者简介：
- 基金信息：
- DOI：10.11918/j.issn.0367-6234.201708010
  CLC： TP302.8
- Published：2018
- 稿件说明：
移动端阅览
LIU Jiaxi, DONG Jian, WU Zhibo, et al. A cooperative failure detector in vehicular cloud computing[J]. 2018, 50(5): 24-29.
DOI：

LIU Jiaxi, DONG Jian, WU Zhibo, et al. A cooperative failure detector in vehicular cloud computing[J]. 2018, 50(5): 24-29. DOI： 10.11918/j.issn.0367-6234.201708010.

摘要

为更好地解决车辆云计算中车辆的高度动态性对失效检测性能的影响，提出了一种适用于车辆云计算环境的基于检测结果共享机制的失效检测器.首先，对车辆云计算的系统架构进行了分析，发现车辆云计算系统具有明显的层次结构，而且可以利用路侧单元对车辆节点进行分组.在此基础之上，引进检测结果共享机制，提出针对车辆云计算环境的共享失效检测器VC-FD.然后，构建了可以对所提出的失效检测器进行定量分析的共享失效检测模型，该模型主要针对检测时间、平均错误发生概率以及检测负载三个失效检测服务质量指标进行评价.最后，在仿真环境下比较和分析了所提出的共享失效检测器与非共享失效检测器的性能.实验结果表明，该失效检测器在保证检测准确性的前提下，通过增加有限的检测负载能够明显地改善系统中节点失效检测时间.因此，提出的基于检测结果共享机制的失效检测器VC-FD能够准确、快速的发现车辆云计算中的节点失效，有效地降低车辆高度动态性对失效检测性能的影响.

Abstract

To solve the problem that the performance of failure detection is effected by mobility of vehicular cloud computing

a new failure detector (VC-FD) based on architecture of vehicular cloud computing was proposed. We found that vehicular cloud computing has a hierarchical structure and the vehicles can be grouped through Roadside Unit (RSU)

according to the architecture analysis of vehicular cloud computing. On this basis

the sharing mechanism of detection results is introduced

and the new failure detector VC-FD for vehicular cloud computing was proposed. Then

the model of cooperative failure detection was proposed to evaluate the detection time

mistake rate and detection overhead. The performance of the VC-FD and non shared failure detector was compared in a simulation environment. The experimental results show that the VC-FD can ensure the accuracy

and significantly improve the node failure detection time by increasing limited detection overhead. Thus

the VC-FD can accurately and quickly find out the node failures in vehicular cloud computing

and effectively reduce the influence of vehicular mobility on the performance of failure detection.

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Related Institution

School of Electronics and Information Engineering, Harbin Institute of Technology

College of Computer Science and Technology, Huaqiao University

School of Computer Science and Engineering, Southeast University

Key Laboratory of Computer Network and Information Integration the Ministry of Education, Southeast University

Fault-tolerant and Mobile Computing Research Center (Harbin Institute of Technology)

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