Human-intelligence workflow management for the big data of augmented reality on cloud infrastructure
- Authors
- Kim, Hyun-Woo; Park, Jong Hyuk; Jeong, Young-Sik
- Issue Date
- 1-Mar-2018
- Publisher
- ELSEVIER SCIENCE BV
- Keywords
- Human-intelligence workflow management; Big data; Cloud infrastructure
- Citation
- NEUROCOMPUTING, v.279, pp 19 - 26
- Pages
- 8
- Indexed
- SCIE
SCOPUS
- Journal Title
- NEUROCOMPUTING
- Volume
- 279
- Start Page
- 19
- End Page
- 26
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/16986
- DOI
- 10.1016/j.neucom.2017.04.082
- ISSN
- 0925-2312
1872-8286
- Abstract
- Human-intelligence workflow management (HIWM) is proposed as a means of dynamically distributing and processing storage work and calculating operations for fast augmented reality (AR) service provision on diverse smart mobile devices based on human behavior to apply the next generation web environments. In HIWM, pre-processing is performed to minimize service response time according to the definition of metadata and user requests for AR services. Basically, to process big data for AR services, a dynamic job distribution scheme is proposed based on the computing capacity of desktops constituting the cloud infrastructures. For final AR services by HIWM, the results of the evaluation of the performance of HIWM in relation to big data processing time are presented. The results show that processing time is 40.56% less than that of the existed methods in proportion to AR service requests. (c) 2017 Elsevier B.V. All rights reserved.
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- Appears in
Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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