TorqueDB: Distributed Querying of Time-Series Data from Edge-local Storage
| Autor: | Dhruv Garg, Prathik Shirolkar, Anshu Shukla, Yogesh Simmhan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Edge device
business.industry Computer science Distributed computing 020206 networking & telecommunications Cloud computing Workload 02 engineering and technology Smart city 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Enhanced Data Rates for GSM Evolution Time series business Edge computing |
| Zdroj: | Euro-Par 2020: Parallel Processing ISBN: 9783030576745 Euro-Par |
| DOI: | 10.1007/978-3-030-57675-2_18 |
| Popis: | The rapid growth in edge computing devices as part of Internet of Things (IoT) allows real-time access to time-series data from 1000’s of sensors. Such observations are often queried to optimize the health of the infrastructure. Recently, edge storage systems allow us to retain data on the edge rather than moving them centrally to the cloud. However, such systems do not support flexible querying over the data spread across 10–100’s of devices. There is also a lack of distributed time-series databases that can run on the edge devices. Here, we propose TorqueDB, a distributed query engine over time-series data that operates on edge and fog resources. TorqueDB leverages our prior work on ElfStore, a distributed edge-local file store, and InfluxDB, a time-series database, to enable temporal queries to be decomposed and executed across multiple fog and edge devices. Interestingly, we move data into InfluxDB on-demand while retaining the durable data within ElfStore for use by other applications. We also design a cost model that maximizes parallel movement and execution of the queries across resources, and utilizes caching. Our experiments on a real edge, fog and cloud deployment show that TorqueDB performs comparable to InfluxDB on a cloud VM for a smart city query workload, but without the associated monetary costs. |
| Databáze: | OpenAIRE |
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