通信学报 ›› 2014, Vol. 35 ›› Issue (5): 49-56.doi: 10.3969/j.issn.1000-436x.2014.05.007

• 学术论文 • 上一篇    下一篇

基于K-means的云化分布式BPEL引擎放置机制

林荣恒,吴步丹,赵耀,杨放春   

  1. 北京邮电大学 网络与交换技术国家重点实验室,北京100876
  • 出版日期:2014-05-25 发布日期:2017-07-24
  • 基金资助:
    国家高技术研究发展计划(“863计划)基金资助项目;国家自然科学基金资助项目

Approach for distributed BPEL engine placement using K-means

Rong-heng LIN,Bu-dan WU,Yao ZHAO,Fang-chun YANG   

  1. State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Online:2014-05-25 Published:2017-07-24
  • Supported by:
    TheNationalHighTechnologyResearchandDevelopmentProgramofChina(863Program);The National Natural Science Foundation of China

摘要:

针对分布式BPEL引擎在云中的放置问题开展研究,提出了一种基于K-means的分布式BPEL引擎放置机制,该机制将BPEL引擎放置问题模型化为相关最优化数学模型,并且将该模型映射到K-means算法进行求解。该机制还讨论了算法在不同网络拓扑随机图、树形网络拓扑的应用。最后利用统计软件R进行了相关实验仿真,仿真结果显示该放置机制可优化服务调用所占用的带宽资源。

关键词: BPEL, 服务引擎, K-means, 分布式计算, 云计算

Abstract:

Aiming to solve the distributed BPEL engine placing problem in cloud, a K-means based distributed BPEL en-gine placing algorithm was proposed. The algorithm transforms the BPEL engine placing model into some optimization model in mathematics, and the optimization problem is solved by K-means algorithm. How to apply the algorithm in dif-ferent network topologies was also discussed, such as random graph and tree network. In the end, statistical software R was used as experiment tool to evaluate the algorithm. Results show that the proposed method can provide a more opti-mized bandwidth usage of combined BPEL service execution.

Key words: BPEL, service engine, K-means, distributed computing, cloud computing

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