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

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.

Authors

Institutions

Publication Details

Journal
International Journal of Cloud Computing
Published
2025-01-01
DOI
https://doi.org/10.1504/ijcc.2025.147442
Primary Topic
Advanced Technology in Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Xiang T.R. Kong, Keqing Guan
International Journal of Cloud Computing
Advanced Technology in Applications
article

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

Xiang T.R. Kong, Keqing Guan
article en

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.

International Journal of Cloud ComputingVol. 14(2)
Dongbei University of Finance and Economics (CN), Liaoning University of International Business and Economics (CN)
Openalex Percentile: Top 74%
Advanced Technology in Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Design of IoT data security storage and allocation model based on cloud and mist integration algorithm — Xiang T.R. Kong, Keqing Guan · International Journal of Cloud Computing (2025) | TGRS Research Map | TGRS