Abstract
The proliferation of sensor devices and services along with the advances in event processing brings many new opportunities as well as challenges for intelligent systems. It is now possible to provide, analyse, and react upon real-time, complex events in smart environments. When existing event services do not provide such complex events directly, an event service composition may be required. However, it is difficult to determine which event service candidates (or service compositions) best suit users’ and applications’ quality-of-service requirements. A sub-optimal service composition may lead to inaccurate event detection and lack of system robustness. In this chapter, we address these issues by first providing a Quality-of-Service (QoS) aggregation schema for complex event service compositions, and then developing a genetic algorithm to create near-optimal event service compositions efficiently. The approach is evaluated with both real sensor data collected via Internet of Things services and synthesised datasets.
| Original language | English |
|---|---|
| Title of host publication | Real-time Linked Dataspaces |
| Subtitle of host publication | Enabling Data Ecosystems for Intelligent Systems |
| Publisher | Springer International Publishing |
| Pages | 169-190 |
| Number of pages | 22 |
| ISBN (Electronic) | 9783030296650 |
| ISBN (Print) | 9783030296643 |
| DOIs | |
| Publication status | Published - 1 Jan 2019 |
Keywords
- Complex event processing
- Dataspaces
- Internet of Things
- Modelling
- Quality-of-service
- Service composition