移动群智感知中基于社区的任务分发算法

龙浩; 张书奎; 张洋; 张力

doi:10.11959/j.issn.1000-436x.2019213

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移动群智感知中基于社区的任务分发算法

学术论文 | 更新时间：2024-06-05

- 移动群智感知中基于社区的任务分发算法
- Task distribution algorithm based on community in mobile crowd sensing
- 通信学报 2019年40卷第10期页码：42-54
- 作者机构：
  
  1. 苏州大学计算机科学与技术学院，江苏苏州 215006
  2. 徐州工业职业技术学院信息与电气工程学院，江苏徐州 221002
- 作者简介：
  
  [ "龙浩（1984- ），男，湖南长沙人，苏州大学博士生、讲师，主要研究方向为群智感知计算、数据挖掘、分布式计算。" ]
  [ "张书奎（1966- ），男，内蒙古呼和浩特人，博士，苏州大学教授、博士生导师，主要研究方向为物联网、无线传感器网络、信息安全、群体感知计算、智能信息处理等。" ]
  [ "张洋（1989- ），男，江苏苏州人，苏州大学硕士生，主要研究方向为物联网、信息安全、群体感知计算、智能信息处理等。" ]
  [ "张力（1983- ），男，江苏镇江人，苏州大学博士生，主要研究方向为群智感知、数据挖掘、并行计算。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61201212);江苏省高等学校自然科学研究面上项目(19KJB520061);徐州市应用基础研究计划基金资助项目(KC17074);苏州市融合通信重点实验室(SKLCC2013XX);江苏省青蓝工程人才培养计划(102508999008);苏州市重点产业技术创新前瞻性应用研究项目(SYG201730)
- DOI：10.11959/j.issn.1000-436x.2019213
  中图分类号： TP393
- 网络出版日期：2019-10，
  
  纸质出版日期：2019-10-25
- 稿件说明：
移动端阅览
龙浩, 张书奎, 张洋, 等. 移动群智感知中基于社区的任务分发算法[J]. 通信学报, 2019,40(10):42-54.

Hao LONG, Shukui ZHANG, Yang ZHANG, et al. Task distribution algorithm based on community in mobile crowd sensing[J]. Journal on communications, 2019, 40(10): 42-54.
龙浩, 张书奎, 张洋, 等. 移动群智感知中基于社区的任务分发算法[J]. 通信学报, 2019,40(10):42-54. DOI： 10.11959/j.issn.1000-436x.2019213.

Hao LONG, Shukui ZHANG, Yang ZHANG, et al. Task distribution algorithm based on community in mobile crowd sensing[J]. Journal on communications, 2019, 40(10): 42-54. DOI： 10.11959/j.issn.1000-436x.2019213.

摘要

针对移动群智感知（MCS）任务分发的有效性和精准性问题，提出了基于社区的任务分发算法。为了解决所提问题，该方法首先通过计算移动节点间的最小生成树、连接参量、社区融合度，抽象和识别出节点的行为模式，将用户合理划分成不同的社区，然后计算感知任务与社区行为模式特征值的匹配度，根据匹配度由社区的中心节点完成任务的分发。仿真结果表明，与其他算法相比，所提方法有效地提高了任务分发的精确性和任务完成率，节约了任务完成的时间成本。

Abstract

A community-based task distribution algorithm was proposed to solve the problem of the validity of mobile crowd sensing (MCS) task distribution.By calculating the minimum spanning tree (MST)

the connection parameter (CP) and the community convergence degree (CI) between the mobile nodes

the behavior patterns of the users were abstracted and identified to rationally divide the nodes into different communities.Then

the eigenvalue matching degree of the community behavior patterns with the sensing task was calculated.According to the matching degree

the distribution of the corresponding tasks was completed by the central node of the community.The simulation results show that the proposed method can effectively improve the accuracy of the task distribution and the task completion rate

and save the time cost of the task completion.

关键词

Keywords

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