上海大学学报(自然科学版)

• 计算机工程与科学 • 上一篇    下一篇

基于云平台的软件服务流体系结构

董贺, 徐凌宇   

  1. 上海大学计算机工程与科学学院, 上海200444
  • 收稿日期:2012-11-26 出版日期:2013-02-28 发布日期:2013-02-28
  • 通讯作者: 徐凌宇(1965—), 男, 教授, 博士生导师, 博士, 研究方向为云计算、数据融合及智能信息处理等. E-mail:xly@shu.edu.cn
  • 作者简介:徐凌宇(1965—), 男, 教授, 博士生导师, 博士, 研究方向为云计算、数据融合及智能信息处理等. E-mail: xly@shu.edu.cn
  • 基金资助:

    国家自然科学基金资助项目(40976108); 国家“十二五”规划课题资助项目(201105033)

SaaS-Flow System Structure Based on Cloud Platform

DONG He, XU Ling-yu   

  1. School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China
  • Received:2012-11-26 Online:2013-02-28 Published:2013-02-28

摘要: 为了对大规模的数据访问和海量海洋信息的处理提供可靠实时的云计算服务, 结合工作流与软件即服务(software-as-a-service, SaaS)的思想, 提出软件服务流的概念, 并构建基于云平台的软件服务流体系结构的系统. 服务流引擎在整个系统中处于底层, 与Hadoop平台进行交互, 运行自行设计的服务流解析与重组算法处理用户请求, 并交付下层执行, 且为上层提供资源表述性转移(representational state transfer, REST)架构风格的服务流监控和资源管理的透明接口, 降低了开发的复杂性, 提高系统的可伸缩性. 用户能够通过Web端访问, 定制个性化软件服务, 并且能实时监控云平台. 在该平台上, 大规模数据访问、高并发以及高密度的访问也是一种常态. 通过构建初步的原型系统, 证明平台体系结构的可用性和高效性.

关键词: Hadoop, RESTful架构, 软件服务流, 云计算, 云平台

Abstract: To provide reliable real-time cloud computing services for large-scale data access and massive marine information processing and by combining the idea of workflow and software-as-a-service (SaaS), a concept of software service flow and build a software service flow architectures system based on a cloud platform is proposed. In this system, a service flow engine is an underlying layer, which interacts with the Hadoop platform. When processing user requests, the engine runs a self-design algorithm which analyses and combines service flow, and is delivered to the underlying layers for execution. Moreover, for the sake of control service flow and manager resource, it also providers many transparent interfaces to the upper layers with representational state transfer (REST) style, thus reducing complexity of development and improving scalability of the system. Users can access the Web page, customize software services, and monitor the cloud platform on real-time. On this platform, large-scale data access, high concurrency, and high-density access are a normal status. By building an initial prototype system, the availability and efficiency of the SaaS-flow system structure is proved.

Key words: Hadoop, cloud computing, cloud platform, representational state transfer (REST) architecture, software-as-a-service (SaaS)-flow

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