The Horus WLAN location determination system
Abstract
We present the design and implementation of the Horus WLAN location determination system. The design of the Horus system aims at satisfying two goals: high accuracy and low computational requirements. The Horus system identifies different causes for the wireless channel variations and addresses them to achieve its high accuracy. It uses location-clustering techniques to reduce the computational requirements of the algorithm. The lightweight Horus algorithm helps in supporting a larger number of users by running the algorithm at the clients.We discuss the different components of the Horus system and its implementation under two different operating systems and evaluate the performance of the Horus system on two testbeds. Our results show that the Horus system achieves its goal. It has an error of less than 0.6 meter on the average and its computational requirements are more than an order of magnitude better than other WLAN location determination systems. Moreover, the techniques developed in the context of the Horus system are general and can be applied to other WLAN location determination systems to enhance their accuracy. We also report lessons learned from experimenting with the Horus system and provide directions for future work.
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Horus uses the simple computation complexity of Bayesian inference method, thus having better performance than SDNNLoc.
“However, Horus uses the simple computation complexity of Bayesian inference method, thus having better performance than SDNNLoc.”
From Embedded Intelligence on FPGA: Survey, Applications and Challenges (2021) · cites this paper as [71]
The SDNNLoc system is more accurate than the other two, with fewer location errors.
“The SDNNLoc system is more accurate than the other two, with fewer location errors.”
From Embedded Intelligence on FPGA: Survey, Applications and Challenges (2021) · cites this paper as [71]
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“The performance evaluation is focused on the runtime of the SDNNLoc and compared with two other baseline systems, which are Horus [71] and DeepFi [72].”
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- Authors
- Youssef, M., & Agrawala, A.
- Affiliations
- University of Maryland, College Park (US)
- ORCID
- Youssef, Moustafa
- Venue
- Proceedings of the 3rd international conference on Mobile systems, applications, and services
- Publisher
- ACM
- Published
- 2005-06-06
- Pages
- 205-218
- OpenAlex
- W2051376734
- Cited by
- 1,653
- References
- 0
- Citations by year
- 2026: 30 · 2025: 52 · 2024: 40 · 2023: 64 · 2022: 69 · 2021: 91 · 2020: 104 · 2019: 146 · 2018: 160 · 2017: 132 · 2016: 119 · 2015: 125 · 2014: 126 · 2013: 71 · 2012: 84
- FWCI
- 61.03
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Mobile Systems, Applications, and Services (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Indoor and Outdoor Localization Technologies
- Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Networks and Protocols
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IPv6, Mobility, Handover, Networks, Security
- Keywords
- indoor positioning, location clustering, positioning accuracy, computational efficiency, testbed evaluation
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