服务发现
计算机科学
服务(商务)
智慧城市
背景(考古学)
服务提供商
万维网
过程(计算)
服务设计
普适计算
光学(聚焦)
差异化服务
计算机安全
数据科学
Web服务
业务
人机交互
地理
物联网
光学
物理
操作系统
营销
考古
作者
Christian Cabrera,Gary White,Andrei Palade,Siobhán Clarke
标识
DOI:10.1109/percom.2018.8444606
摘要
Smart cities provide software services to citizens that are likely to be deployed in large, dynamic, heterogeneous, and distributed environments. The discovery of these services needs to be efficient and pervasive, based on the specific context of the city, and the integration of diverse providers. We identify a trade-off between accuracy and performance in the discovery of services in this scenario. Existing research has proposed solutions that focus either on semantic methods to improve accuracy with performance negatively affected, or vice versa. Additionally, the composition of services from different sources has not been explored in smart cities and large scenarios. We propose to address the trade-off by extending both how service information is organised, and the service discovery process. Service organisation uses urban context to spread service descriptions to the right urban-places; the service discovery process uses this model to forward requests where they are more likely to be solved. We simulate our model as a network of gateways that covers Dublin city center and manages services information. Results show that our model solves more requests than previous work in a smart city environment. In addition, response time keeps acceptable even when there are 100 thousand services.
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