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A novel distributed Social Internet of Things service recommendation scheme based on LSH forest

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Abstract

For the Social Internet of Things (SIoT), the interaction among ever increasing number of smart devices results in an exponential increase of services, which leads to an extreme difficulty for users to find suitable services. To address this issue, most existing recommendation algorithms are based on the data stored on the centralized server and distributed schemes are ignored. Meanwhile, distributed recommendation algorithms face the problems of privacy leakage and efficiency, which decrease the quality of experience (QoE). Therefore, we propose a novel SIoT service recommendation scheme called SIoT- SR, which adopts LSH Forest while combining with collaborative filtering algorithm to predict the Quality of Service (QoS) data of users. The LSH forest implements binary search by sorting and also has the ability to self-correct parameters. It can achieve a good tradeoff among memory, accuracy, efficiency, and privacy. Finally, we validate the effectiveness of the scheme based on the dataset WS-DREAM. The experimental results show that SIoT-SR has high prediction accuracy and efficiency while saving computing resources and are suitable for service recommendation of SIoT with resource-constrained devices.

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Funding

This work is supported by the NSF of China under Grant Nos. 61672321, 61832012, 61771289, and 61373027.

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Authors and Affiliations

  1. School of Information Science and Engineering, Qufu Normal University, Rizhao, 276826, Shandong, China

    Biwei Yan & Honglu Jiang

  2. School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250253, Shandong, China

    Jiguo Yu & Meihong Yang

  3. Shandong Computer Science Center (National Supercomputer Center in Jinan), Jinan, 250014, China

    Jiguo Yu & Meihong Yang

  4. School of Computer Science and Technology, Shandong University, Qingdao, 266237, China

    Zhiguo Wan

  5. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, Shandong, China

    Lina Ni

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  1. Biwei Yan
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  2. Jiguo Yu
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  3. Meihong Yang
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  4. Honglu Jiang
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  5. Zhiguo Wan
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  6. Lina Ni
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Correspondence to Jiguo Yu.

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Yan, B., Yu, J., Yang, M. et al. A novel distributed Social Internet of Things service recommendation scheme based on LSH forest. Pers Ubiquit Comput 25, 1013–1026 (2021). https://doi.org/10.1007/s00779-019-01283-4

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  • DOI: https://doi.org/10.1007/s00779-019-01283-4

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