Efficient data retrieval for large-scale smart city applications through applied Bayesian inference

Jin Ming Koh; Marcus Sak; Hwee Xian Tan; Huiguang Liang; Fachmin Folianto; Tony Quek

doi:10.1109/ISSNIP.2015.7106930

Efficient data retrieval for large-scale smart city applications through applied Bayesian inference

Jin Ming Koh, Marcus Sak, Hwee Xian Tan, Huiguang Liang, Fachmin Folianto, Tony Quek

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

Recent years have witnessed the proliferation of worldwide efforts towards developing technologies for enabling smart cities, to improve the quality of life for citizens. These smart city solutions are typically deployed across large spatial regions over long time scales, generating massive volumes of data. An efficient way of data retrieval is thus required, for post-processing of the data-such as for analytical and visualization purposes. In this paper, we propose a data prefetching and caching algorithm based on Bayesian inference, for the retrieval of data in large-scale smart city applications. A brute-force approach is used to determine the optimal weight correction factor in the proposed prefetching algorithm. We evaluate the optimized Bayesian prefetching algorithm against the Naïve and Random prefetch baselines, using both simulated and actual data usage patterns. Results show that the Bayesian approach can achieve up to 48.4% reductions in actual user-perceived application delays during data retrieval.

Original language	English
Title of host publication	2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479980550
DOIs	https://doi.org/10.1109/ISSNIP.2015.7106930
Publication status	Published - 2015 May 13
Event	10th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015 - Singapore, Singapore Duration: 2015 Apr 7 → 2015 Apr 9

Publication series

Name	2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015

Conference

Conference	10th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015
Country	Singapore
City	Singapore
Period	15-04-07 → 15-04-09

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering
Computer Networks and Communications
Information Systems

Access to Document

10.1109/ISSNIP.2015.7106930

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Koh, J. M., Sak, M., Tan, H. X., Liang, H., Folianto, F., & Quek, T. (2015). Efficient data retrieval for large-scale smart city applications through applied Bayesian inference. In 2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015 [7106930] (2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSNIP.2015.7106930

Koh, Jin Ming ; Sak, Marcus ; Tan, Hwee Xian ; Liang, Huiguang ; Folianto, Fachmin ; Quek, Tony. / Efficient data retrieval for large-scale smart city applications through applied Bayesian inference. 2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015. Institute of Electrical and Electronics Engineers Inc., 2015. (2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015).

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title = "Efficient data retrieval for large-scale smart city applications through applied Bayesian inference",

abstract = "Recent years have witnessed the proliferation of worldwide efforts towards developing technologies for enabling smart cities, to improve the quality of life for citizens. These smart city solutions are typically deployed across large spatial regions over long time scales, generating massive volumes of data. An efficient way of data retrieval is thus required, for post-processing of the data-such as for analytical and visualization purposes. In this paper, we propose a data prefetching and caching algorithm based on Bayesian inference, for the retrieval of data in large-scale smart city applications. A brute-force approach is used to determine the optimal weight correction factor in the proposed prefetching algorithm. We evaluate the optimized Bayesian prefetching algorithm against the Na{\"i}ve and Random prefetch baselines, using both simulated and actual data usage patterns. Results show that the Bayesian approach can achieve up to 48.4% reductions in actual user-perceived application delays during data retrieval.",

author = "Koh, {Jin Ming} and Marcus Sak and Tan, {Hwee Xian} and Huiguang Liang and Fachmin Folianto and Tony Quek",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE. Copyright: Copyright 2015 Elsevier B.V., All rights reserved.; 10th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015 ; Conference date: 07-04-2015 Through 09-04-2015",

year = "2015",

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doi = "10.1109/ISSNIP.2015.7106930",

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series = "2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015",

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Koh, JM, Sak, M, Tan, HX, Liang, H, Folianto, F & Quek, T 2015, Efficient data retrieval for large-scale smart city applications through applied Bayesian inference. in 2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015., 7106930, 2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015, Institute of Electrical and Electronics Engineers Inc., 10th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015, Singapore, Singapore, 15-04-07. https://doi.org/10.1109/ISSNIP.2015.7106930

Efficient data retrieval for large-scale smart city applications through applied Bayesian inference. / Koh, Jin Ming; Sak, Marcus; Tan, Hwee Xian; Liang, Huiguang; Folianto, Fachmin; Quek, Tony.

2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7106930 (2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Folianto, Fachmin

AU - Quek, Tony

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Koh JM, Sak M, Tan HX, Liang H, Folianto F, Quek T. Efficient data retrieval for large-scale smart city applications through applied Bayesian inference. In 2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7106930. (2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015). https://doi.org/10.1109/ISSNIP.2015.7106930