Living in the present
Living in the present
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活在当下
DOI：
10.1145/2168697.2168703
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Eyers D
中科院分区：
文献类型：
--
作者：
Eyers D
如今的社交网络平台，如Facebook、Twitter、Google+和LinkedIn，越来越多地需要即时处理大量用户生成的数据。随着这些平台的角色从主要是历史数据的门户转变为提供实时数据分析的平台，我们观察到它们的体系结构逐渐从基于分布式数据管理技术的以存储为中心的设计，towardsevent-我们认为，现在是时候从根本上重新思考社交网络平台的软件架构，并将其建立在一个基于内容的通信模型，明确设计用于在服务器集群上传播和划分传入请求流。因此，基于内容的发布/订阅系统充当可伸缩的、弹性的、高度响应的数据分发骨干。通过专注于新数据，这种架构可以优化数据的路由以匹配数据中心的拓扑结构，动态地调整数据流以缓解热点，并在计算昂贵的实时数据分析应用程序需要时弹性地扩展到更多服务器。
Today's social web platforms, such as Facebook, Twitter, Google+, and LinkedIn, increasingly have to process large volumes of user-generated dataon the fly. As the role of such platforms shifts from being portals for largely historic data towards providing platforms for real-time data analytics, we observe that their architectures incrementally move fromstorage-centricdesigns, based on distributed data management technologies, towardsevent-basedmodels exploiting queueing and stream processing systems.We believe that it is time to rethink fundamentally the software architecture for social web platforms and base them on a content-based communication model, that is explicitly designed to disseminate and partition incoming request flows on a cluster of servers. A content-based publish/subscribe system thus acts as a scalable and elastic, highly responsive data distribution backbone. By focusing on fresh data, such an architecture can optimize the routing of data to match the topology of the data center, dynamically adapt data flows to alleviate hot spots, and elastically scale to more servers when required by computationally expensive on-the-fly data analytics applications.
影响因子：
0.5
作者：
Carel, Havi
通讯作者：
Carel, Havi