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Distributed Service Discovery Algorithm Based on Ant Colony Algorithm

机译:基于蚁群算法的分布式服务发现算法

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摘要

UDDI is a universal description, discovery and integration protocol. As a public registry of Web service, it is designed to store information about each company and its service. Traditional centralized service discovery structure of UDDI service registration center does not apply to large-scale service discovery. When all the services register to a center, the service bottleneck, failure of single point and the poor scalability defects will occur. In addition, traditional service matching mechanisms are mainly based on keywords method which lacks of semantic description and makes the service publisher and demanders cannot reach a common semantic understanding. This will lead to the problems of semantic conflicts and low accuracy that seriously affects the precision and recall of service matching. To address these shortcomings of the centralized service discovery structure of UDDI, we propose a distributed semantic service registration center which is in the construction of loosely coupled P2P network enabled the progressive massive search. In the P2P distributed network, there can be a large number of nodes to store the registration information which is suitable for large-scale service because of the adaptivity, scalability and good fault tolerance characteristics. In order to reduce the number of concurrent transmitted packets, the advanced ant colony algorithm is introduced to forward packets by probabilistic choice. The results comparison with the traditional algorithm is given through the simulation experiments and it has shown that the proposed method has good performance for the distributed service discovery.
机译:UDDI是一种通用的描述,发现和集成协议。作为Web服务的公共注册中心,它旨在存储有关每个公司及其服务的信息。 UDDI服务注册中心的传统集中式服务发现结构不适用于大规模服务发现。当所有服务注册到中心时,将出现服务瓶颈,单点故障和可伸缩性差的缺陷。另外,传统的服务匹配机制主要基于关键词方法,缺乏语义描述,使得服务发布者和需求者无法达成共识。这将导致语义冲突和准确性低下的问题,严重影响服务匹配的准确性和召回性。为了解决UDDI集中式服务发现结构的这些缺点,我们提出了一个分布式语义服务注册中心,该中心在构建能够进行渐进式大规模搜索的松耦合P2P网络中。在P2P分布式网络中,由于适应性,可伸缩性和良好的容错特性,可能存在大量的节点来存储注册信息,这适合于大规模服务。为了减少并发传输数据包的数量,引入了先进的蚁群算法通过概率选择来转发数据包。通过仿真实验,与传统算法进行了比较,结果表明该方法在分布式服务发现中具有良好的性能。

著录项

  • 来源
    《Journal of software》 |2014年第1期|70-75|共6页
  • 作者单位

    College of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun,China Key Laboratory of Logistics Industry Economy and Intelligent Logistics at Universities of Jilin Province, Changchun, China;

    College of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun, China;

    College of Communication Engineering, Jilin University, Changchun, China;

    College of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun,China;

    College of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun,China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    UDDI; P2P distributed network; Semantic; Ant colony algorithm;

    机译:UDDI;P2P分布式网络;语义蚁群算法;

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