Name
Abstract | ||
|---|---|---|
Abundant sensors and smart devices deployed in the Internet of Things pose the potential for IoT applications to detect high-level meaningful events. Complex Event Processing technology offers solutions of event pattern(complex event) queries over streams in real time well timely. Yet when CEP is detecting complex events that are continuous for some time, it results in detecting out multiple reduplicate pattern matches, leading to the burden of high output throughput and unnecessary disturb to IoT applications. In this paper, we propose an efficient Event-Feedback Mechanism, to eliminate these reduplicate pattern matches via letting the first detected complex event feedback to the input stream and detecting each selected event based on "evenly spaced time window" and Poisson distribution. The Event-Feedback Mechanism is shown to achieve over three orders of magnitude performance in relieving output throughput, and a range of tested scenarios compared to a significant algorithm proves it practical and effective. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-22047-5_26 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
CEP,The Internet of Things,Event-feedback mechanism,Reduplicate pattern matches,Continuous complex events | Data mining,Computer science,Internet of Things,Complex event processing,Real-time computing,Throughput,Poisson distribution | Conference |
Volume | ISSN | Citations |
9196 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingyue Cui | 1 | 1 | 0.35 |
| Chunhong Zhang | 2 | 14 | 6.37 |
| Yuewen Su | 3 | 1 | 0.35 |
| Yang Ji | 4 | 127 | 27.38 |