Ah Sue J, Brand P, Falk J, Hasholzner R, Teich J (2019)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2019
Publisher: Springer
City/Town: New York, NY, USA
Pages Range: 1-12
Conference Proceedings Title: HCII 2019 Late Breaking Work Papers Proceedings
Event location: Orlando, Florida, USA
DOI: 10.1007/978-3-030-30033-3_10
As 5G wireless communication technology will be deployed in the next few years, an increasing amount
of data becomes available from mobile devices tested out in the field. Exploiting this data, recent
investigations show the potential to improve the wireless modem design and performance using data-
centric approaches, e.g., power optimization with machine learning (ML) algorithms [1]. As depicted in
Figure 1, such data-centric workflows are exploratory and iterative by nature. For instance, time pattern
identification is performed by domain experts to derive assumptions on potential optimizations and these
assumptions are continuously refined during multiple iterations of data collection and exploration. In this
context, we propose 3 ideas to increase the exploration speed: (i) a methodology to minimize the data
pre-processing duration in each iteration, (ii) a novel entropy-based data interaction technique for visual
event sequence exploration and (iii) a similarity measure to perform subsequence matching in order to
identify frequent modem behaviors to be optimized.
APA:
Ah Sue, J., Brand, P., Falk, J., Hasholzner, R., & Teich, J. (2019). Optimizing Exploratory Workflows for Embedded Platform Trace Analysis and its Application to Cellular Modems. In HCII 2019 Late Breaking Work Papers Proceedings (pp. 1-12). Orlando, Florida, USA, US: New York, NY, USA: Springer.
MLA:
Ah Sue, Jonathan, et al. "Optimizing Exploratory Workflows for Embedded Platform Trace Analysis and its Application to Cellular Modems." Proceedings of the 21st Int. Conf. on Human-Computer Interaction, Orlando, Florida, USA New York, NY, USA: Springer, 2019. 1-12.
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