A Compressed, Inference-enabled Encoding Scheme for RDF Stream Processing

Abstract : The number of sensors producing data streams at a high velocity keeps increasing. This paper describes an attempt to design an inference-enabled, distributed, fault-tolerant framework targeting RDF streams in the context of an industrial project. Our solution gives a special attention to the latency issue, an important feature in the context of providing reasoning services. Low latency is attained by compressing the scheme and data of processed streams with a dedicated semantic-aware encoding solution. After providing an overview of our architecture, we detail our encoding approach which supports a trade-off between two common inference methods, i.e., materialization and query reformula-tion. The analysis of results of our prototype emphasize the relevance of our design choices.
Complete list of metadatas

Cited literature [14 references]  Display  Hide  Download

https://hal-upec-upem.archives-ouvertes.fr/hal-01740502
Contributor : Olivier Curé <>
Submitted on : Thursday, March 22, 2018 - 9:26:53 AM
Last modification on : Thursday, July 5, 2018 - 2:45:46 PM
Long-term archiving on : Thursday, September 13, 2018 - 7:12:25 AM

File

compressed-inference-enabled.p...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01740502, version 1

Citation

Jérémy Lhez, Xiangnan Ren, Badre Belabbess, Olivier Curé. A Compressed, Inference-enabled Encoding Scheme for RDF Stream Processing. ESWC, 2017, Portorož, Slovenia. ⟨hal-01740502⟩

Share

Metrics

Record views

69

Files downloads

197