Title :
PSTEP - A Novel Probabilistic Event Processing Language for Uncertain Spatio-temporal Event Streams of Internet of Vehicles
Author :
Huiyong Li;Yuanrui Zhang;Yixiang Chen
Author_Institution :
MoE Eng. Res. Center for Software/Hardware Co.-design Technol. &
Abstract :
Internet of Vehicles (IoV, shortly) is a typical system of Internet of Things. Spatio-Temporal event stream is one of basic features of IoV. These event streams often are uncertain due to the limit of the monitoring device and the high speed of vehicles. Developing an event processing language to process these spatio-temporal event streams with uncertainty is a challenge issue. The goal of this paper is to develop a Probabilistic Event Processing Language, called as Probabilistic Spatio-Temporal Event Processing language (PSTEP, shortly), dealing with this challenge issue. In PSTEP, we use the Possible World Model to express uncertain spatio-temporal events of IoV and assign a spatio-temporal event with a probability which is the threshold value for processing the existence of an event. We establish its syntax and operational semantics. Finally, a case study is given to show the effectiveness of the PSTEP language.
Keywords :
"Data models","Spatial databases","Probabilistic logic","Monitoring","Intelligent vehicles","Internet of things","Syntactics"
Conference_Titel :
Software Quality, Reliability and Security - Companion (QRS-C), 2015 IEEE International Conference on
DOI :
10.1109/QRS-C.2015.43