Energy efficient techniques for iot application on resource aware fog computing paradigm

Published

20-03-2025

DOI:

https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.2.11

Keywords:

Resource aware, IoT application, fog computing paradigm, latency, network, Energy Efficient Technique

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Issue

Section

Research article

Authors

  • K. Mohamed Arif Khan Department of Computer Science, Jamal Mohamed College (Autonomous), (Affiliated to Bharathidasan University), Tiruchirappalli, Tamil Nadu, India.
  • A.R. Mohamed Shanavas Department of Computer Science, Jamal Mohamed College (Autonomous), (Affiliated to Bharathidasan University), Tiruchirappalli, Tamil Nadu, India.

Abstract

During the rapid emergence of the IoT environment, computing is widespread in all domains and undergoes tiny changes on an everyday basis that lead to momentous shifts in the development and deployment of applications. Network infrastructure can be utilized efficiently in large volumes of data by deploying the applications. IoT applications constitute different types of modules that run together with interdependency and run on the cloud conventionally in the data center. The research study proposes a framework for a resource-aware fog computing paradigm using a Module mapping algorithm, lower bound algorithm, Application Module and Network Node and resource-aware algorithm. Fog computing is employed for deploying IoT applications that are sensitive to latency. The incoming data is processed by fog computing by utilizing the available resources by reducing the amount of data sent to the server. The optimum performance can be achieved by connecting the appropriate sensor node to the parent node. The proposed algorithm reduces energy consumption and latency. Comparative analysis is performed for the proposed and conventional fog computing paradigm.

How to Cite

Khan, K. M. A., & Shanavas, A. M. (2025). Energy efficient techniques for iot application on resource aware fog computing paradigm. The Scientific Temper, 16(02), 3792–3802. https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.2.11

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