A Green and Secure Model for Fog Computing in Mobile Cloud Environments Using Containerization

Internet of Things devices, and mobile computing, there is a growing demand for effective data processing where computation meets network traffic. Here, the fog computing concept has emerged to cater to this demand through a decentralized architecture that allows the processing and storing of data closer to end-users. Despite this, the dynamic and diverse fog computing ecosystem delivers security threats and resource efficiency challenges. This article introduces a solution for it, called the Green and Secure Model for Fog Computing in Mobile Cloud Environments, by implementing container architecture. Containers allow applications with dependencies to be bundled together for improved portability, scalability, and resource utilization models such as GSM-FCMCE. Moreover, the model contains an intelligent security layer where encryption and data- authentication and access control paradigms-help protect volatile information from malicious attacks. In addition, the proposed model adopts green computing techniques to minimize energy utilization and increase sustainability in fog-based environments. By performing many experiments and simulations, the efficiency in terms of security achieved based on the GSM-FCMCE model works to minimize energy waste rate and increase resource utilization. It would seem quite a viable model for the cloud computing community to solve some of these fog-related issues and introduce more sustainable & secure mobile data processing.

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Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/autocom64127.2025.10956335
Primary Topic
IoT and Edge/Fog Computing
Type
article
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article

A Green and Secure Model for Fog Computing in Mobile Cloud Environments Using Containerization

Danish Kundra, B. Ankayarkanni, Bichitrananda Patra, Kalyan Acharjya et al.
IoT and Edge/Fog Computing
article

A Green and Secure Model for Fog Computing in Mobile Cloud Environments Using Containerization

Danish Kundra, B. Ankayarkanni, Bichitrananda Patra, Kalyan Acharjya, Kanika Seth, Mithun Kumar S
article en

Abstract

Internet of Things devices, and mobile computing, there is a growing demand for effective data processing where computation meets network traffic. Here, the fog computing concept has emerged to cater to this demand through a decentralized architecture that allows the processing and storing of data closer to end-users. Despite this, the dynamic and diverse fog computing ecosystem delivers security threats and resource efficiency challenges. This article introduces a solution for it, called the Green and Secure Model for Fog Computing in Mobile Cloud Environments, by implementing container architecture. Containers allow applications with dependencies to be bundled together for improved portability, scalability, and resource utilization models such as GSM-FCMCE. Moreover, the model contains an intelligent security layer where encryption and data- authentication and access control paradigms-help protect volatile information from malicious attacks. In addition, the proposed model adopts green computing techniques to minimize energy utilization and increase sustainability in fog-based environments. By performing many experiments and simulations, the efficiency in terms of security achieved based on the GSM-FCMCE model works to minimize energy waste rate and increase resource utilization. It would seem quite a viable model for the cloud computing community to solve some of these fog-related issues and introduce more sustainable & secure mobile data processing.

Jain University (IN), Siksha O Anusandhan University (IN), Maharishi University of Management and Technology (IN), Sathyabama Institute of Science and Technology (IN), Chitkara University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 93%
IoT and Edge/Fog Computing
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A Green and Secure Model for Fog Computing in Mobile Cloud Environments Using Containerization — Danish Kundra, B. Ankayarkanni, et al. · (2025) | TGRS Research Map | TGRS