Journal on Communications ›› 2014, Vol. 35 ›› Issue (Z1): 65-71.doi: 10.3969/j.issn.1000-436x.2014.z1.013

• Virtualization and cloud computing • Previous Articles     Next Articles

PSO based task scheduling for medical big data

Chao HU1,Jun PENG2,Wen-tao YU2   

  1. 1 School of Public Health,Information and Network Center,Central South University,Changsha 410083,China
    2 School of Information Science and Engineering,Central South University,Changsha 410075,China
  • Online:2014-10-25 Published:2017-06-19
  • Supported by:
    the National Natural Science Foundation of China

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.

Key words: medical big data, task scheduling, particle swarm

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