Modeling and management of usage-aware distributed datasets for global Smart City Application Ecosystems
Modeling and management of usage-aware distributed datasets for global Smart City Application Ecosystems
复制标题
全球智慧城市应用生态系统的使用感知分布式数据集的建模和管理
DOI：
10.7717/peerj-cs.115
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
S. Dustdar
中科院分区：
文献类型：
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作者：
Johannes M. Schleicher;Michael Vögler;Christian Inzinger;S. Dustdar
当今智慧城市产生的数据量不断增长，为城市利益相关者和第三方创建的新型应用程序提供了巨大的潜力。当前的智慧城市应用模型大多假设数据由其原始应用和位置专有管理并绑定到其原始应用和位置。我们认为，智慧城市数据必须不限于这种数据孤岛，以便未来的智慧城市应用可以无缝访问和集成来自多个城市的多个来源的数据。在本文中，我们提出了一种方法和工具集，用于对可用的智慧城市数据源进行建模，并在智慧城市环境中实现高效的分布式数据访问。我们引入了一个建模抽象来描述智能城市数据源的结构和相关属性，例如安全性和合规性约束，沿着技术不可知的独立访问子集。基于这种抽象，我们提出了一个中间件工具集，通过自主重新定位可用数据源的相关子集，以提高基于可配置机制的智能城市应用程序的服务质量，实现高效和无缝的数据访问。我们评估我们的方法使用的情况下，一个分布式的城市基础设施决策支持系统的案例研究，并表明，数据子集的选择性迁移可以显着减少应用程序的响应时间。分布式与并行计算，软件工程
The ever-growing amount of data produced by and in today’s smart cities offers significant potential for novel applications created by city stakeholders as well as third parties. Current smart city application models mostly assume that data is exclusively managed by and bound to its original application and location.We argue that smart city datamust not be constrained to such data silos so that future smart city applications can seamlessly access and integrate data frommultiple sources across multiple cities. In this paper, we present a methodology and toolset to model available smart city data sources and enable efficient, distributed data access in smart city environments. We introduce a modeling abstraction to describe the structure and relevant properties, such as security and compliance constraints, of smart city data sources along with independently accessible subsets in a technology-agnostic way. Based on this abstraction, we present a middleware toolset for efficient and seamless data access through autonomous relocation of relevant subsets of available data sources to improve Quality of Service for smart city applications based on a configurable mechanism. We evaluate our approach using a case study in the context of a distributed city infrastructure decision support system and show that selective relocation of data subsets can significantly reduce application response times. Subjects Distributed and Parallel Computing, Software Engineering