.png){kind=icon}
返回
Simplifying CPS Application Development through Fine-grained, Automatic Timeout Predictions
.png){kind=icon}
PRE
AI
DOI：10.1145/3385960.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Application development for Cyber Physical Systems (CPS) is challenging, because the wireless network and the devices introduce latencies that vary continuously along with the load, status, or environmental conditions of the infrastructure. Reactive programming is well suited for the development of event-driven applications, yet current reactive programming frameworks require developers to predict event arrival timeboundaries at compile time, which is impractical, if not impossible, for CPS. Thus, there is a tradeoff between timeliness and completeness of complex event computations, e.g., operational efficiency in a manufacturing plant: Waiting too long until all individual events arrive can fail to produce a useful result, while not waiting long enough may lead to faults due to incomplete status information. In this article, we propose (a) a set of extensions to state-of-the-art reactive programming frameworks, which remove the burden of specifying timeouts at compile time by utilizing (b) Khronos, a middleware that automatically determines timeouts by taking into account variations in event arrival times due to the underlying infrastructure. Evaluation on a physical testbed shows that the extensions significantly decrease developer effort and that Khronos considerably improves timeliness under varying network configurations and conditions, while still satisfying the application's tolerance to missed events.
Keyword:
Cyber-physical systems
late arrivals
middleware
time management
event-driven programming
reactive programming
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.1
论文数:
896
被引数:
1.9K
机构
引用论文
Intravenous Adenosine but Not Its First Metabolite Inosine Provokes Chest Pain in Healthy Volunteers
OAAI
OAAI分享收藏Multiple-mouse magnetic resonance imaging with cryogenic radiofrequency probes for evaluation of brain development.png)
NeuroImageOAAI
NeuroImageIF0
OAAI分享收藏分享收藏
查看更多内容