BROWSE
Detail
Journal Article
PCCP: A prefetched fingerprint data-based continuous convergence positioning framework for performance improvement in urban environments
- Authors
- Jiwoo Han, Jaejun Yoo, Daesub Yoon
- Issue Date
- 2025-08
- Citation
- ETRI Journal, v.권호미정, pp.1-12
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원
- Language
- English
- Type
- Journal Article
- Abstract
- Positioning systems play a critical role in urban environments, where accurately determining a user's location is essential for a wide range of applications. Managing vast and diverse datasets such as Wi-Fi, Bluetooth, and image-based fingerprints poses significant performance challenges, particularly in data-intensive urban areas. In this paper, we introduce a novel framework, called PCCP, which is specifically designed to enhance the performance of positioning systems through a predictive prefetching mechanism. We construct fingerprint dependency graphs based on historical access values and define access patterns, and then prefetch relevant fingerprint data for near-future requests to minimize latency. We present a formal algorithm for integrating the prefetching mechanism into the positioning system and implementing it on a client-server architecture. Experimental results highlight the effectiveness of the proposed PCCP in optimizing fingerprint data management, leading to faster and more efficient positioning services.
- KSP Keywords
- Access pattern, Client-server architecture, Data Management, Dependency graphs, IEEE 802.11(Wi-Fi), Image-based, Performance challenges, Positioning services, continuous convergence, data-based, data-intensive
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
