面向医疗大数据任务低时延需求的路径计算方案

张夏童 1; 任智源 1; 胡锦涛 1; 张怡 2; 张海林 1

doi:10.7652/xjtuxb202002015

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面向医疗大数据任务低时延需求的路径计算方案

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- 面向医疗大数据任务低时延需求的路径计算方案
- A Path Computing Scheme for Low-Latency Requirement of Medical Big Data Task
- 西安交通大学学报 2020年54卷第2期页码：119-126
- 作者机构：
  
  西安电子科技大学综合业务网理论及关键技术国家重点实验室,西安,710071
- 作者简介：
- 基金信息：
  
  : 2019-08-29。作者简介: 张夏童(1996—),男,硕士生;任智源(通信作者),男,副教授,硕士生导师。基金项目: 国家重点研发计划资助项目(SQ2016YFHZ02150)
- DOI：10.7652/xjtuxb202002015
  中图分类号： TM912
- 网络首发：2020-02-10，
  
  纸质出版：2020
- 稿件说明：
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张夏童 1, 任智源 1, 胡锦涛 1, 等. 面向医疗大数据任务低时延需求的路径计算方案[J]. 西安交通大学学报, 2020,54(2):119-126.

A Path Computing Scheme for Low-Latency Requirement of Medical Big Data Task[J]. 2020, 54(2): 119-126.
张夏童 1, 任智源 1, 胡锦涛 1, 等. 面向医疗大数据任务低时延需求的路径计算方案[J]. 西安交通大学学报, 2020,54(2):119-126. DOI： 10.7652/xjtuxb202002015.

A Path Computing Scheme for Low-Latency Requirement of Medical Big Data Task[J]. 2020, 54(2): 119-126. DOI： 10.7652/xjtuxb202002015.

摘要

针对云计算应用于医疗大数据处理时存在的通信高负荷及任务处理高时延的问题

提出一种面向低时延任务需求的路径计算方案。该方案首先将医疗大数据任务构建为由多个具有输入输出关系的子任务所组成的有向无环图; 然后

设计了一种云雾网络架构

利用医院中的交换机、路由器等网络边缘设备组成雾计算层

在端到端的定向数据传输过程中利用雾节点的计算能力逐步完成医疗大数据任务计算。为将医疗大数据任务部署至医院网络

提出一种基于离散二值粒子群优化(BPSO)算法的任务映射策略

将有向无环图形式的大数据任务映射至医院雾网络拓扑图

为任务数据寻找合适的计算路径

并最小化医疗大数据任务处理时延。仿真结果表明

当数据量取5～10 Mb时

应用路径计算方案的任务处理时延相比云计算可降低50%以上。

Abstract

A path computing scheme for low-latency task is proposed to solve the problem that there exist high communication load and high task processing latency when cloud computing is applied to medical big data processing. The scheme firstly constructs the medical big data task into a directed acyclic graph that is composed of multiple subtasks with explicit input and output relationships. Then

a cloud and fog network architecture is designed

in which network edge devices such as switches and routers in hospitals form a fog computing layer. The computing capacity of fog nodes is used to gradually complete the big data task in the process of end-to-end directional data transmission. A task mapping strategy based on the discrete binary particle swarm optimi-ation(BPSO)algorithm is proposed to deploy the medical big data task to a hospital network. The big data task in the form of a directed acyclic graph is mapped into a topology graph of the hospital fog network to find an appropriate comput

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