A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT
A novel enhanced quantum particle swarm optimization algorithm for IIoT deployments is proposed. It provides enhanced connectivity, reduced energy consumption, and optimized delay. We consider heterogeneous scenarios of network topologies for optimal path configuration by exploring and exploiting th...
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doaj-4f3bf47f547147088fc5644d06da71bf2021-10-05T23:00:44ZengIEEEIEEE Access2169-35362021-01-01913402213403610.1109/ACCESS.2021.31150269546795A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoTSheetal N. Ghorpade0https://orcid.org/0000-0002-3292-8044Marco Zennaro1https://orcid.org/0000-0002-0578-0830Bharat S. Chaudhari2https://orcid.org/0000-0003-2401-8996Rashid A. Saeed3https://orcid.org/0000-0002-9872-081XHesham Alhumyani4S. Abdel-Khalek5RMD Sinhgad School of Engineering, Savitribai Phule Pune University, Pune, IndiaScience, Technology and Innovation Unit, Abdus Salam International Centre for Theoretical Physics, Trieste, ItalySchool of Electronics and Communication Engineering, MIT World Peace University, Pune, IndiaDepartment of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi ArabiaDepartment of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi ArabiaDepartment of Mathematics, College of Science, Taif University, Taif, Saudi ArabiaA novel enhanced quantum particle swarm optimization algorithm for IIoT deployments is proposed. It provides enhanced connectivity, reduced energy consumption, and optimized delay. We consider heterogeneous scenarios of network topologies for optimal path configuration by exploring and exploiting the hunts. It uses multiple inputs from heterogeneous IIoT into quantum and bio-inspired optimization techniques. The differential evolution operator and crossover operations are used for information interchange among the nodes to avoid trapping into local minima. The different topology scenarios are simulated to study the impact of <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-degrees of connectivity concerning objective functions’ evaluation and compared with existing techniques. The results demonstrate that our algorithm consumes a minimum of 30.3% lesser energy. Furthermore, it offers improved searching precision and convergence swiftness in the possible search space for <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-disjoint paths and reduces the delay by a minimum of 26.7%. Our algorithm also improves the throughput by a minimum of 29.87% since the quantum swarm inclines to generate additional diverse paths from multiple source nodes to the gateway.https://ieeexplore.ieee.org/document/9546795/Connectivityenergy consumptionIndustrial Internet of ThingsoptimizationPSOQPSO |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sheetal N. Ghorpade Marco Zennaro Bharat S. Chaudhari Rashid A. Saeed Hesham Alhumyani S. Abdel-Khalek |
spellingShingle |
Sheetal N. Ghorpade Marco Zennaro Bharat S. Chaudhari Rashid A. Saeed Hesham Alhumyani S. Abdel-Khalek A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT IEEE Access Connectivity energy consumption Industrial Internet of Things optimization PSO QPSO |
author_facet |
Sheetal N. Ghorpade Marco Zennaro Bharat S. Chaudhari Rashid A. Saeed Hesham Alhumyani S. Abdel-Khalek |
author_sort |
Sheetal N. Ghorpade |
title |
A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT |
title_short |
A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT |
title_full |
A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT |
title_fullStr |
A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT |
title_full_unstemmed |
A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT |
title_sort |
novel enhanced quantum pso for optimal network configuration in heterogeneous industrial iot |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
A novel enhanced quantum particle swarm optimization algorithm for IIoT deployments is proposed. It provides enhanced connectivity, reduced energy consumption, and optimized delay. We consider heterogeneous scenarios of network topologies for optimal path configuration by exploring and exploiting the hunts. It uses multiple inputs from heterogeneous IIoT into quantum and bio-inspired optimization techniques. The differential evolution operator and crossover operations are used for information interchange among the nodes to avoid trapping into local minima. The different topology scenarios are simulated to study the impact of <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-degrees of connectivity concerning objective functions’ evaluation and compared with existing techniques. The results demonstrate that our algorithm consumes a minimum of 30.3% lesser energy. Furthermore, it offers improved searching precision and convergence swiftness in the possible search space for <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-disjoint paths and reduces the delay by a minimum of 26.7%. Our algorithm also improves the throughput by a minimum of 29.87% since the quantum swarm inclines to generate additional diverse paths from multiple source nodes to the gateway. |
topic |
Connectivity energy consumption Industrial Internet of Things optimization PSO QPSO |
url |
https://ieeexplore.ieee.org/document/9546795/ |
work_keys_str_mv |
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1716841599038652416 |