大数据服务深度需求与SOA协作集成的异构系统融合机制

Heterogeneous Fusion Mechanism With SOA Collaboration Integration Based on Big Data Service Deep Requirements

摘要:

大数据服务需求的认知深度和服务架构的融合度直接影响多业务大数据应用的资源管理和服务质量,提出了一种基于大数据服务深度需求分析和面向服务的协作集成架构的异构系统融合机制；该机制,一方面,在分析大数据源多样化、差异化大数据组织形式及其存储方式,基于开放性大数据服务上下文,以及上下文集合的关联匹配与大数据服务分析的映射关系,结合不同类型用户的需求差异化特征,建立了大数据服务需求分析模型；另一方面,对于多态异构的移动互联网大数据服务,经过结构化和开放性处理后,给出大数据通信和服务调用描述定义,提出了SOA协作集成的异构系统融合架构；仿真实验结果表明,所提出的算法在大数据服务响应成功率、执行时间和代价比等方面具有明显优势。

Abstract:

The cognitive depth of big data service demand and Integration of service architecture would affect the resource management and service quality of big data application, the heterogeneous fusion mechanism with SOA collaboration integration based on big data service deep requirements was proposed in this paper. On the one hand, based on the analysis of big data source diversification, differentiation of big data organization and storage methods, open big data service context and the mapping relation between contexts set associative matching and big data service analysis, the demand analysis model of big data service is established according to the different needs of different types of users. On the other hand, for the mobile Internet Heterogeneous data services association, through structured and open treatment, given the big data communication and service description definition, a SOA collaborative heterogeneous system integration architecture was proposed. The simulation results show that the proposed algorithm has obvious advantages in terms of the success rate, execution time and cost ratio of large data services.