A survey of real-time approximate nearest neighbor query over streaming data for fog computing
| Autor: | Mahdi Rabbani, Yanchao Li, Yongli Wang, Hamed Jelodar, Isma Masood, Chi Yuan, Xiaohui Jiang, Peng Hu |
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| Rok vydání: | 2018 |
| Předmět: |
Computer Networks and Communications
Computer science business.industry Dimensionality reduction Quantization (signal processing) Big data Hash function 02 engineering and technology computer.software_genre Theoretical Computer Science k-nearest neighbors algorithm Artificial Intelligence Hardware and Architecture Fog computing 020204 information systems Streaming data 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining business computer Computer Science::Databases Software |
| Zdroj: | Journal of Parallel and Distributed Computing. 116:50-62 |
| ISSN: | 0743-7315 |
| DOI: | 10.1016/j.jpdc.2018.01.005 |
| Popis: | Real-time approximate nearest neighbor (ANN) query over streaming data in fog computing environment is the fundamental problem of real-time analysis of big data. As the fog computing paradigm needs to provide real-time and low latency services, and traditional streaming data ANN query technology cannot be directly applied. Exploring the basic theory, querying framework and technology of real-time ANN query over streaming data for fog computing becomes one of the current research hotspots. This paper summarizes the related ANN query technology based on random hash, learning-to-hash and synopses, analyzes the problems and challenges of real-time ANN query in resource-limited fog computing environment, and finally discusses in detail the basic theory and method of the query, the dimension reduction and encoding method based on learning-to-hash, the generating synopses method for ANN query over streaming data from Internet of Thing, and the future related research directions of ANN query framework and others. Additionally, we propose a Dynamic Adaptive Quantization (DAQ) method for learning-to-hash. Experiments show that DAQ outperformed other quantization methods. |
| Databáze: | OpenAIRE |
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