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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Published on: September 8, 2023

Energy efficient service placement in fog computing.

Usha Vadde¹, Vijaya Sri Kompalli²

¹Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradash, India.

Peerj. Computer Science

|September 12, 2022

Summary

This study introduces an optimized module placement strategy for fog computing environments. The improved JAYA approach significantly reduces energy consumption in Internet of Things applications by 31%.

Keywords:

Energy consumption Fog computing Internet of Things Service placement

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Area of Science:

Computer Science
Distributed Systems
Cloud Computing

Background:

The Internet of Things (IoT) generates vast data, requiring efficient processing.
Cloud computing faces latency challenges due to geographical distance from IoT devices.
Fog computing offers a solution by distributing resources closer to IoT devices.

Purpose of the Study:

To address the challenge of optimal application module placement in heterogeneous fog environments.
To minimize energy consumption within fog computing landscapes.
To enhance the efficiency of fog-enabled IoT applications.

Main Methods:

An improved JAYA optimization approach was developed for module placement.
Simulations were conducted using the iFogSim toolkit.
Performance was evaluated based on energy consumption, network usage, delays, and execution time.

Main Results:

The proposed JAYA approach demonstrated significant reductions in energy consumption.
Average energy consumption decreased by 31% compared to existing methods.
The approach also showed improvements in network usage, delays, and execution time.

Conclusions:

The enhanced JAYA approach provides an effective solution for optimal module placement in fog computing.
This method significantly reduces energy consumption for fog-enabled IoT applications.
The findings contribute to more efficient and sustainable fog computing infrastructures.