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Shortest Path Discovery in Consideration of Obstacle in Mobile Social Network Environments

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Abstract

The issue of shortest path discovery in consideration of obstacle is one of the problems for location-based services in mobile social network environments. Currently, most research focuses on quickly discovering the shortest path in obstacle free area with reasonable latency, while the obstacle issue, especially the obstacles that enter temporarily is not fully considered. This creates the need for investigation on shortest path discovery at the same time avoiding detected obstacles. In this paper, a shortest path discovery approach is proposed. The following contributions are made: (1) Modeling the shortest path discovery problem in consideration of obstacle. (2) Discovering the shortest path using an improved A-star algorithm with reasonable latency. (3) Evaluating the accuracy rate of shortest path discovery with acceptable latency for a location-based service in a mobile social network. Experimental results conclusively demonstrate the efficiency and effectiveness of the proposed approach.

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Acknowledgment

This work is supported by the National Natural Science Foundation of China under Grant No. 61602428 and 61370132; the Fundamental Research Funds for the Central Universities under Grant No. 2652015338.

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Correspondence to Dawei Sun .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Sun, D., Qu, W., Gao, S., Liu, L. (2018). Shortest Path Discovery in Consideration of Obstacle in Mobile Social Network Environments. In: Romdhani, I., Shu, L., Takahiro, H., Zhou, Z., Gordon, T., Zeng, D. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 252. Springer, Cham. https://doi.org/10.1007/978-3-030-00916-8_58

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  • DOI: https://doi.org/10.1007/978-3-030-00916-8_58

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00915-1

  • Online ISBN: 978-3-030-00916-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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