PSO based task scheduling for medical big data

Chao HU; Jun PENG; Wen-tao YU

doi:10.3969/j.issn.1000-436x.2014.z1.013

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PSO based task scheduling for medical big data

Virtualization and cloud computing | 更新时间：2024-06-05

- PSO based task scheduling for medical big data
- Journal on Communications Vol. 35, Issue Z1, Pages: 65-71(2014)
- 作者机构：
  
  1. 中南大学公共卫生学院信息与网络中心，湖南长沙 410083
  2. 中南大学信息科学与工程学院，湖南长沙 410075
- 作者简介：
- 基金信息：
  
  the National Natural Science Foundation of China(61379111)
- DOI：10.3969/j.issn.1000-436x.2014.z1.013
  CLC： TP391
- Online First：2014-10，
  
  Published：25 October 2014
- 稿件说明：
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Chao HU, Jun PENG, Wen-tao YU. PSO based task scheduling for medical big data[J]. Journal on Communications, 2014, 35(Z1): 65-71.
DOI：

Chao HU, Jun PENG, Wen-tao YU. PSO based task scheduling for medical big data[J]. Journal on Communications, 2014, 35(Z1): 65-71. DOI： 10.3969/j.issn.1000-436x.2014.z1.013.

摘要

摘要：在医疗信息共享平台下，选取一种合适的任务调度策略完成医疗数据查询任务在各医院内的调度分配，是医疗大数据处理所需解决的重要问题。为了保证任务调度时间最短和成本最低，提出一种改进的粒子群算法。该算法构造了时间最优和成本最优双适应度函数，自适应地调整粒子速度更新的惯性权重，加快搜寻最优粒子的速度，并求解出最合理的数据查询任务调度方案，最大限度地提高医疗信息共享平台中医疗数据查询的效率。实验结果验证了所提出算法的有效性。

Abstract

How to select a suitable task scheduling strategy to accomplish the task of medical data query in scheduling and allocation inside each hospital is a important problem demanded to be dealt with in medical big data processing.In order to content the optimal medical data corresponding time and optimal cost considered in task scheduling

a improved particle swarm algorithm was proposed.The algorithm constructs the dual fitness function of optimal time and optimal cost to adjusted the inertia weight of the update of particle velocity adaptively

fasten the speed of optimal particle searching

and find out the most reasonable task scheduling scheme of data query

maximize the efficiency of medical data query in medical information sharing platform.Experiment results demonstrate the effectiveness of the proposed algorithm.

关键词

Keywords

references

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