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Efficient caching method in fog computing for internet of everything

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Abstract

Recently Internet of Everything has emerged as integration of various IoT machines to which cloud computing provide storage to data and processing power to the geographically distributed IoT devices. In order to boost the efficiency of the system and Quality of Service(QoS), fog layer is added in the existing cloud infrastructure. Due to continuous increase in the time sensitive applications, reduction in latency is a crucial issue in the fog computing paradigm. Therefore, the main objective of this work is to reduce the latency in fog computing. To achieve this objective, popularity based caching is performed in this work by majorly focusing on the interest of the users. In this context, first clustering of the IoT devices is performed on the basis of their interests and distance between them using spectral clustering technique and then each cluster is mapped with the fog node such that caching of the popular files is done effectively. To further reduce the latency, in case of cache miss, the Device to Device (D2D) communication is used. Finally, association rules are also used to predict the future demands of the IoT devices. Performance analysis of the proposed scheme shows that the proposed method outperforms the other existing caching methods.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Hamirpur, Himachal Pradesh, India

    Riya & Nitin Gupta

  2. Department of Information Technology, Netaji Subhas University of Technology, Dwarka, New Delhi, India

    Sanjay Kumar Dhurandher

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  1. Riya
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  2. Nitin Gupta
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  3. Sanjay Kumar Dhurandher
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Correspondence to Nitin Gupta.

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This article is part of the Topical Collection: Special Issue on P2P Computing for Beyond 5G Network and Internet-of-Everything

Guest Editors: Prakasam P, Ajayan John, Shohel Sayeed

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Riya, Gupta, N. & Dhurandher, S.K. Efficient caching method in fog computing for internet of everything. Peer-to-Peer Netw. Appl. 14, 439–452 (2021). https://doi.org/10.1007/s12083-020-00952-z

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