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A shortest path planning algorithm for cloud computing environment based on multi-access point topology analysis for complex indoor spaces

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Abstract

Due to the increasing complexity of internal spaces and dynamic change in certain specific partitions in large indoor areas, indoor navigation has become more important as it is useful to help people find their destination or evacuate from dangerous areas. A shortest path planning method is the main technique used in an indoor navigation system. Hence, we proposed a shortest path planning algorithm based on multi-access point topological analysis for a dynamically changing indoor navigation path. To support the dynamically changing characteristics, we pre-construct an indoor route when the route is requested. Further, we dynamically update its internal path information when the route changes. The proposed method is suitable for both simple and complex large-scale indoor spaces, even when the related indoor maps are difficult to be used for navigation. We conduct a performance evaluation to compare the proposed method with the current research approaches. The results show that our method provides improved performance for indoor navigation.

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Acknowledgments

This research was supported by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (2012M3C4A7032781).

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Correspondence to Byeong-Seok Shin.

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Li, Y., Park, JH. & Shin, BS. A shortest path planning algorithm for cloud computing environment based on multi-access point topology analysis for complex indoor spaces. J Supercomput 73, 2867–2880 (2017). https://doi.org/10.1007/s11227-016-1650-x

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  • DOI: https://doi.org/10.1007/s11227-016-1650-x

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