Sensory data profoundly influences the quality of detected events in a distributed complex event processing system (DCEP). Since each sensor’s status is unstable at runtime, a single sensing assignment is often insufficient to fulfill the consumer’s quality requirements. In this paper, we study in the context of AQuA-CEP the problem of dynamic quality monitoring and adaptation of complex event processing by active integration of suitable data sources. To support this, in AQuA-CEP, queries to detect complex events are supplemented with consumer-definable quality policies that are evaluated and used to autonomously select (or even configure) suitable data sources of the sensing infrastructure. In addition, we studied different forms of expressing quality policies and analyzed how it affects the quality monitoring process. Various modes of evaluating and applying quality-related adaptations and their impacts on correlation efficiency are addressed, too. We assessed the performance of AQuA-CEP in IoT scenarios by utilizing the notion of the quality policy alongside the query processing adaptation using knowledge derived from quality monitoring. The results show that AQuA-CEP can improve the performance of DCEP systems in terms of the quality of results while fulfilling the consumer’s quality requirements. Quality-based adaptation can also increase the network’s lifetime by optimizing the sensor’s energy consumption due to efficient data source selection.
|Titel||The 17th ACM International Conference on Distributed Event-Based Systems (DEBS 2023)|
|Status||Accepted/In press - 14-mrt.-2023|
|Evenement||The 17th ACM International Conference on Distributed and Event-Based Systems (DEBS'23) - University of Neuchatel, Neuchatel, Switzerland|
Duur: 27-jun.-2023 → 30-jun.-2023
|Conference||The 17th ACM International Conference on Distributed and Event-Based Systems (DEBS'23)|
|Periode||27/06/2023 → 30/06/2023|