Sustainable Energy Management System Using Green Smart Grid in Mobile Cloud Computing Environment

Biswas, Asmita; Jakovits, Pelle; Roy, Deepsubhra Guha

doi:10.1007/978-3-031-08038-8_7

Cited by 1 publication

(1 citation statement)

References 39 publications

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“…Furthermore, combining Mobile cloud computing (MCC) with the Green Smart Grid (GSG) provides trustworthy energy management as well as costeffective data sharing between end-users and service providers [39]. Furthermore, the use of cloud computing technologies such as HDFS, MapReduce, and H-base in a smart distribution network cloud platform enables for the rapid storage and processing of power data while also ensuring data security and integrity [40]. These advancements in cloud computing contribute to the overall sustainability and efficiency of the electrical grid.…”

Section: Prior Studiesmentioning

confidence: 99%

Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach

2024

IJIES

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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the applying sigmoid fish swarm optimization (SiFSO) for early compromised device detection and subsequently alerting other network nodes. Additionally, our data center implements an innovative ant skyscape architecture (ASA) cooling mechanism, departing from traditional, unsustainable cooling strategies that harm the environment. To validate the effectiveness of these approaches, extensive simulations were conducted. The evaluations primarily revolved around the fish colony's ability to detect compromised devices, focusing on source tracing, realistic modelling, and an impressive 98% detection accuracy rate under ASA cooling solution with 0.16 ºC within 1,300 second. Compromised devices pose a substantial risk to green data centers, as attackers could manipulate and disrupt network equipment. Therefore, incorporating cyber enhancements into the green data center concept is imperative to foster more adaptable and efficient smart networks.

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Section: Prior Studiesmentioning

confidence: 99%

Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach

2024

IJIES

View full text Add to dashboard Cite

show abstract

Sustainable Energy Management System Using Green Smart Grid in Mobile Cloud Computing Environment

Cited by 1 publication

References 39 publications

Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach

Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach

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