Title: Design of IoT data security storage and allocation model based on cloud and mist integration algorithm

Authors: Keqing Guan; Xianli Kong

Addresses: Institute for Big Data Research, Liaoning University of International Business and Economics, Dalian, 116052, China ' School of Economics, Dongbei University of Finance and Economics, Dalian, 116025, China

Abstract: As internet and communication technology evolve, the industrial internet of things (IIoT) has rapidly developed. However, existing IIoT systems struggle to ensure the timely and secure transmission of user data. This study introduces a cloud fog hybrid network architecture and establishes a latency and data security model for individual users, employing an improved ant colony algorithm for minimising latency under security constraints. For multi-user scenarios, software-defined networks enhance the architecture, and a refined allocation model is developed. Experiments indicate that, at 500 iterations, the root mean square errors (RMSE) for various algorithms were 0.51, 0.43, 0.28, and 0.14, respectively. With five users and a data volume of 50 MB, the latencies observed were 24, 22, 18, and 14 seconds, respectively. These findings demonstrate that the proposed method effectively secures data storage and reduces latency in IIoT environments.

Keywords: industrial internet of things; IIoT; fog computing; cloud computing; data security; time delay; root mean square errors; RMSE.

DOI: 10.1504/IJCC.2025.147442

International Journal of Cloud Computing, 2025 Vol.14 No.2, pp.200 - 214

Received: 13 Mar 2025
Accepted: 16 Apr 2025
Published online: 15 Jul 2025 *

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