Many IoT application domains can be naturally modelled as a graph representing the interactions between devices, sensors and their environment. In this context, Thing'in is an Orange initiated platform managing a graph of millions of connected (IoT) and non-connected objects using a commercial graph database. The graph of Thing'in embeds a dynamic behaviour due to the fact that IoT devices create temporary connections between each other and with their surroundings. Analyzing the history of these connections paves the way to new promising applications such as object tracking, anomaly detection and forecasting the future behaviour. However, existing commercial graph databases are not designed with a native temporal support which limits their usability in such use cases. This motivated us to implement a temporal graph management system from the ground up.
The main contribution of this thesis resides in taking a holistic approach to covering query languages as well as the physical storage, query processing and generation of temporal graphs which lead to the design of our temporal graph management system Clock-G. This system is composed of a temporal graph query language that can express a wide range of temporal queries with a user-friendly and succinct syntax. Another key component of Clock-G is our proposed storage technique that can significantly reduce the space usage while maintaining query lantency. We also proposed a query processor that can optimise the evaluation of temporal queries using our proposed storage technique.
The evaluation of our system validates the efficiency of the proposed techniques and motivates our choice of building a graph system with native temporal support.
Julia STOYANOVICH New York University
Francois GOASDOUE Université de Rennes 1
Angela BONIFATI Université Lyon 1
Gabor SZARNYAS CWI Amsterdam
Dan VODISLAV CY TECH
Philippe RAIPIN PARVEDY Orange Labs