A Dynamic Load-balancing Method for Distributed RDF Stream Processing Systems
Toshiyuki Hirakata, Toshiyuki Amagasa · 2021
This paper proposes a method for multi-query optimization for distributed RDF stream processing systems. Due to the recent advances of IoT (internet of things) and CPS (cyber-physical systems), the edge computing environment becomes rich in computational resources, and the popularity of RDF stream has been increasing due to its high expressivity. To deal with massive RDF streams on the server-side, distributed RDF stream systems have been intensively studied, where many user queries are processed simultaneously using multiple computing nodes. For making query processing more efficient, it is important to cope with the changes of RDF streams in data rate and data distribution. However, the state-of-the-art methods cannot cope with it. To this problem, we propose a cost model for distributed RDF query processing and a dynamic load-balancing method based on the model. The experimental study shows that the proposed method outperforms the existing method even when the data rate and data distribution of RDF stream changes.