International Journal of Leading Research Publication

E-ISSN: 2582-8010   •   Impact Factor: 9.56

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 June 2025 Submit your research before last 3 days of to publish your research paper in the issue of June.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 6 Issue 6
June 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Quantum-Inspired Heuristics for Optimizing Cloud Infrastructure Usage

Author(s) Srikanth Jonnakuti
Country United States
Abstract The age of multi-region cloud computing, optimal resource-packing and task scheduling are key to realizing the highest system performance as well as lowered operational expense. This paper examines the use of quantum-inspired approximation algorithms (QIAAs) in the form of QAOA-like methodologies to mitigate large-scale resource assignment and scheduling complications in heterogeneous, multi-tenant cloud systems. Drawn from the concepts of quantum mechanics, these algorithms take advantage of probabilistic modeling and superposition to traverse multiple solution spaces with minimal waste. Unlike traditional heuristics, QIAAs demonstrate faster convergence rate and resilience, especially in NP-hard scheduling problems involving constraints across geographical areas, latency, energy efficiency, and Service Level Agreements (SLAs). The research involves hybrid models like quantum-inspired gravitational search, binary chaotic salp swarm, and hyper-heuristic QIAAs, comparing them with conventional evolutionary algorithms. Real-time simulations illustrate significant improvements in throughput, energy usage, and QoS measurements. Close attention is paid to the task prioritization and adaptive decision-making processes integrated into these models. The results confirm the scalability and adaptability of QIAAs in dealing with fluctuating workloads and optimizing compute resource use in geographically distributed cloud environments. Overall, this research serves as a blueprint for the incorporation of quantum-inspired optimization in cloud schedulers for next-generation ready clouds, setting the path towards next-gen intelligent cloud orchestration systems.
Field Engineering
Published In Volume 5, Issue 6, June 2024
Published On 2024-06-07
Cite This Quantum-Inspired Heuristics for Optimizing Cloud Infrastructure Usage - Srikanth Jonnakuti - IJLRP Volume 5, Issue 6, June 2024. DOI 10.70528/IJLRP.v5.i6.1557
DOI https://doi.org/10.70528/IJLRP.v5.i6.1557
Short DOI https://doi.org/g9nhrb
View / Download PDF File

Share this



CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJLRP DOI prefix is
10.70528/IJLRP

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 5 Isu 12 Cover Page Vol 5 Isu 11 Cover Page Vol 5 Isu 10

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJLRP
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijlrp.com