A scalable framework for secure and reliable wireless-based fog cloud communication

—Wireless telecommunication systems are essential in transferring data through fog cloud servers. However, the fog cloud servers suffer from unreliable and non-secure routing and limited power resources when mobile users are mobile. This paper introduces a scalable framework (SFRRDC) for reliable wireless routing and secure data transfer. We aim to address security and reliability issues by combining pheromone termite (PT) characteristics and ant colony optimization (ACO) algorithms for high-performance, more secure, highly reliable data transfer among the fog cloud servers. For that, the proposed SFRRDC supports a user authentication mining (UAM) algorithm to secure the confidentiality of the users. Based on testing results, it is confirmed that the proposed SFRRDC provides a better solution for confidentiality and fast routing for a wireless telecommunication system. The results show that the proposed SFRRDC framework’s energy consumption outperforms competing frameworks’ energy consumption with a better-achieved latency. For example, the suggested SFRRDC method uses 748.5 Joules during 72 hours of operation, competing frameworks use more energy, and DDFQFR uses 976.22 Joules. It also shows that the proposed SFRRDC is immune to malicious attacks. The results show that with 3,600 Fog cloud users, the proposed HEE protocol reduces the number of attacks to only 48 compared to 58, 72, and 77415 expected malicious attacks when using the ICDRP-F-SDVN, ACO, and DDFQFR frameworks, respectively.

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Publication Details

Journal
Measurement Sensors
Published
2024-12-04
DOI
https://doi.org/10.1016/j.measen.2024.101408
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.35
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article

A scalable framework for secure and reliable wireless-based fog cloud communication

Joon Yoo, Abdul Razaque, Gulnara Bektemyssova, Kymbat Khairosheva
1 citations
Measurement Sensors
IoT and Edge/Fog Computing
0.35
article

A scalable framework for secure and reliable wireless-based fog cloud communication

Joon Yoo, Abdul Razaque, Gulnara Bektemyssova, Kymbat Khairosheva
article en
1 citations

Abstract

—Wireless telecommunication systems are essential in transferring data through fog cloud servers. However, the fog cloud servers suffer from unreliable and non-secure routing and limited power resources when mobile users are mobile. This paper introduces a scalable framework (SFRRDC) for reliable wireless routing and secure data transfer. We aim to address security and reliability issues by combining pheromone termite (PT) characteristics and ant colony optimization (ACO) algorithms for high-performance, more secure, highly reliable data transfer among the fog cloud servers. For that, the proposed SFRRDC supports a user authentication mining (UAM) algorithm to secure the confidentiality of the users. Based on testing results, it is confirmed that the proposed SFRRDC provides a better solution for confidentiality and fast routing for a wireless telecommunication system. The results show that the proposed SFRRDC framework’s energy consumption outperforms competing frameworks’ energy consumption with a better-achieved latency. For example, the suggested SFRRDC method uses 748.5 Joules during 72 hours of operation, competing frameworks use more energy, and DDFQFR uses 976.22 Joules. It also shows that the proposed SFRRDC is immune to malicious attacks. The results show that with 3,600 Fog cloud users, the proposed HEE protocol reduces the number of attacks to only 48 compared to 58, 72, and 77415 expected malicious attacks when using the ICDRP-F-SDVN, ACO, and DDFQFR frameworks, respectively.

Measurement SensorsVol. 37
Gachon University (KR), Intelligent Systems Research (United States) (US), International Information Technologies University (KZ)
Openalex Percentile: Top 36%
IoT and Edge/Fog Computing
0.35
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A scalable framework for secure and reliable wireless-based fog cloud communication — Joon Yoo, Abdul Razaque, et al. · Measurement Sensors (2024) | TGRS Research Map | TGRS