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Modeling and management of usage-aware distributed datasets for global Smart City Application Ecosystems

机译：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

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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 data must not be constrained to such data silos so that future smart city applications can seamlessly access and integrate data from multiple 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.
机译：如今，智慧城市及其内部不断增长的数据量为城市利益相关者以及第三方创建的新颖应用提供了巨大潜力。当前的智慧城市应用程序模型大多假设数据仅由其原始应用程序和位置管理并绑定到其原始应用程序和位置。我们认为，智慧城市数据一定不能局限于此类数据孤岛，以使未来的智慧城市应用程序可以无缝访问和集成来自多个城市中多个来源的数据。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。我们引入了建模抽象，以技术不可知的方式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以及可独立访问的子集。基于此抽象，我们提出了一种中间件工具集，该工具集可通过自动重定位可用数据源的相关子集来进行高效，无缝的数据访问，从而基于可配置的机制提高智能城市应用程序的服务质量。我们在一个分布式城市基础设施决策支持系统的背景下使用案例研究评估了我们的方法，并表明选择性地重定位数据子集可以显着减少应用程序响应时间。

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