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A service recovery method based on trust evaluation in mobile social network

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Abstract

Mobile social network makes users create and share multimedia contents freely and conveniently. However, some nodes in mobile social network have malicious behavior, such as discarding or tampering packet. These factors will cause service interruptions in the process of providing multimedia contents for the user. When the service interruption happens, how to choose the more reliable backup device, reduce interruption number, increase the packet transmission efficiency and improve user’s experience of sharing multimedia contents is the object of this paper. We propose a service recovery method based on trust evaluation which adopts Dempster-Shafer (D-S) evidence theory. The service requester calculates the direct trust degree and the recommended trust degree of the backup devices, then uses the evidence combination rule to calculate the comprehensive trust degree. The backup device with the highest trust value will be seclected to recover the service. The simulation results show that this method effectively improves the packet delivery ratio, reduces the service execution time and provides users with more stable multimedia contents.

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Acknowledgments

The work is supported by National Natural Science Foundation of China (61302078, 61372108, 61370220), Program for Innovative Research Team (in Science and Technology) in University of Henan Province Grant (15IRTSTHN010).

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Authors and Affiliations

  1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Danmei Niu, Lanlan Rui, Haoqiu Huang & Xuesong Qiu

  2. Information Engineering College, Henan University of Science and Technology, Luoyang, 471023, China

    Danmei Niu

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  1. Danmei Niu
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  2. Lanlan Rui
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  3. Haoqiu Huang
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  4. Xuesong Qiu
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Correspondence to Danmei Niu.

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Niu, D., Rui, L., Huang, H. et al. A service recovery method based on trust evaluation in mobile social network. Multimed Tools Appl 76, 3255–3277 (2017). https://doi.org/10.1007/s11042-016-3963-4

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  • DOI: https://doi.org/10.1007/s11042-016-3963-4

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