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论文类型：期刊论文

发表时间：2017-01-12

发表刊物：NEUROCOMPUTING

收录刊物：SCIE、EI、Scopus

卷号：220

页面范围：60-66

ISSN号：0925-2312

关键字：Hybrid load; Online e-health service; Compression index; Storm platform

摘要：Hybrid load in e-health services is composed of online e-health service applications and offline jobs. Previous methods overlooked the impact of system performance for the fine-grained service components. In this paper, a hybrid load scheduling scheme is proposed in which scheduling is performed not only at the level of the component, but also within components. To improve both execution efficiency and searching accuracy, the proposed algorithm searches the compressing method of the Lucene index and then filters that index. Simulations are conducted on a Storm platform to evaluate the performance of the proposed scheme. Simulation results demonstrate that the proposed scheme can increase the response speed by 67.79% with an accuracy of 95.94%, and the response speed decreases by 11.6-53.2%. (C) 2016 Elsevier B.V. All rights reserved.