SmartProvenance: User‐friendly provenance system for internet of things applications based on event flow graphs - Byeong‐Mo Chang; Kyung‐Min Lee; Ga‐Young Koh; Kwanghoon Choi (IET Software)
Abstract Internet of things (IoT) applications called SmartApps are event‐driven programs running on the SmartThings cloud. To understand the behaviour of SmartApps, users may have questions regarding which execution flows follow particular events or why specific actions occur. However, checking internal programme behaviours, such as event‐driven execution flows, is more difficult for users because SmartApps run on the cloud. In this paper, we propose SmartProvenance, which is a provenance system for IoT applications and provides a graphical user interface (GUI) environment for provenance queries on event flow graphs. The event flow graph of a SmartApp visualises all execution control flows initiated by events, which are constructed by performing static programme analysis. The graph is decorated with dynamically collected event and action information in the GUI interface for provenance queries. Then, users can query the provenance by simply clicking on the graph. An event flow graph as the form of a GUI for queries in the SmartProvenance system allows users to view IoT services by all possible event flow paths in a SmartApp. Thus, the provenance information being visualised on the event flow graph can be intuitively understood in the context of IoT services. Therefore, users can answer provenance questions themselves without difficulty.