| Title |
Modeling and management of usage-aware distributed datasets for global Smart City Application Ecosystems |
| ID_Doc |
45764 |
| Authors |
Schleicher, JM; Vögler, M; Inzingerz, C; Dustdar, S |
| Title |
Modeling and management of usage-aware distributed datasets for global Smart City Application Ecosystems |
| Year |
2017 |
| Published |
|
| DOI |
10.7717/peerj-cs.115 |
| Abstract |
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. |
| Author Keywords |
Smart city application engineering; Data management; Data migration; Quality of service |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000425418800001 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
https://peerj.com/articles/cs-115.pdf
|