In:
International Journal of Distributed Sensor Networks, SAGE Publications, Vol. 15, No. 8 ( 2019-08), p. 155014771986866-
Abstract:
This article overviews the emerging use of deep neural networks in data analytics and explores which type of underlying hardware and architectural approach is best used in various deployment locations when implementing deep neural networks. The locations which are discussed are in the cloud, fog, and dew computing (dew computing is performed by end devices). Covered architectural approaches include multicore processors (central processing unit), manycore processors (graphics processing unit), field programmable gate arrays, and application-specific integrated circuits. The proposed classification in this article divides the existing solutions into 12 different categories, organized in two dimensions. The proposed classification allows a comparison of existing architectures, which are predominantly cloud-based, and anticipated future architectures, which are expected to be hybrid cloud-fog-dew architectures for applications in Internet of Things and Wireless Sensor Networks. Researchers interested in studying trade-offs among data processing bandwidth, data processing latency, and processing power consumption would benefit from the classification made in this article.
Type of Medium:
Online Resource
ISSN:
1550-1477
,
1550-1477
DOI:
10.1177/1550147719868669
Language:
English
Publisher:
SAGE Publications
Publication Date:
2019
detail.hit.zdb_id:
2192922-1
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