云环境下的流式空间信息服务

Streaming spatial information services under cloud computing

随着物联网、传感器技术与应用的发展,对大规模多维空间数据集成与服务的需求愈加迫切。如何实现基于大规模、多维空间数据流的实时计算成为空间数据处理领域的难点。结合云计算的特点,提出针对高速、大流量空间数据的实时处理方法。通过对多维、异构空间数据进行智能处理,生成结构化、简洁化的中间属性集;利用针对高速数据流的大规模数据实时处理方法,解决Map/Reduce难以满足此类计算实时性要求的不足。在此基础上,设计了流式空间信息组织模型与云端适配方法,对方法中的关键技术问题进行了描述。实践表明,该方法可显著提高动态空间信息的服务质量与运行性能。

Wireless sensor networks and the internet of things have become popular.The demand for integration and service of large-scale and multi-dimensional spatial data is still pressing.However,real-time service in the large scale spatial data flow remains a challenge and hotspot for spatial data processing research and development.Considering the characteristics of cloud computing,this paper proposes a method for large scale data processing under high speed data stream.By intelligent processing of multi-dimensional and heterogeneous spatial data,the concise,structured,intelligent middle of property is generated.Based on a method for large scale data processing under high speed data stream,the difficulty of Map/Reduce to meet real-time requirements of such calculations in adequate has been solved.Further,the organization model of streaming spatial information,in addition,the key technical problems in the method are described.Ultimately,the experimental result is encouraging and indicates that the method can significantly improve service quality and operational performance of dynamic spatial information.