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Data Scheduling Method of Social Network Resources Based on Multi-Agent Technology

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Multimedia Technology and Enhanced Learning (ICMTEL 2020)

Abstract

Aiming at the problem that the traditional scheduling method can’t deal with a large number of data quickly when dealing with social network resource data, a new scheduling method of social network resource data based on multi-Agent technology is proposed. Firstly, the social network scheduling framework is designed, using the two-level structure of Agent and three CDN management domains to hide the distribution and heterogeneity of different resources, setting the upper limit trigger conditions of data in each management domain of the framework, using reasoning tools to infer and calculate the SLA comprehensive level of each network operation node, calculating the proportion difference between various resources, selecting the appropriate bias a two-stage resource scheduling method is used to realize resource data scheduling. The experimental results show that: compared with the traditional scheduling method, the social network resource data scheduling method based on multi-Agent technology can maintain the processing time in about 10 s with the increase of data volume, and the processing time is shorter, which is more suitable for practical use.

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Correspondence to Xing-hua Lu .

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Lu, Xh., Zeng, Lf., Huang, Hh., Yan, Wh. (2020). Data Scheduling Method of Social Network Resources Based on Multi-Agent Technology. In: Zhang, YD., Wang, SH., Liu, S. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-030-51100-5_13

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  • DOI: https://doi.org/10.1007/978-3-030-51100-5_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-51099-2

  • Online ISBN: 978-3-030-51100-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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