Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling

Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling

Abstract This paper presents a new approach based on Boltzmann Distribution and Bayesian Optimization to solve the energy-efficient resource allocation in edge computing. It employs Bayesian Optimization to optimize the parameters iteratively for the minimum energy consumption and latency. Coupled w...

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Bibliographic Details
Main Authors: Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Idrees Alsolbi
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Edge computing
Resource scheduling
Boltzmann distribution
Bayesian framework
Energy optimization
Latency reduction
Online Access:https://doi.org/10.1038/s41598-025-16317-6
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