Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing
The Internet of Things (IoT) faces significant challenges in the requirements of sensitive task latency, reasonable resource allocation and reliability for resource transactions. This paper introduces a novel method for road resource allocation in the IoT context of connected and autonomous electric...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/13/2997 |
| _version_ | 1797591835338604544 |
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| author | Yibo Han Zheng Zhang Pu Han Bo Yuan Lu Liu John Panneerselvam |
| author_facet | Yibo Han Zheng Zhang Pu Han Bo Yuan Lu Liu John Panneerselvam |
| author_sort | Yibo Han |
| collection | DOAJ |
| description | The Internet of Things (IoT) faces significant challenges in the requirements of sensitive task latency, reasonable resource allocation and reliability for resource transactions. This paper introduces a novel method for road resource allocation in the IoT context of connected and autonomous electric vehicles (CAEVs). The proposed algorithm leverages the ant colony algorithm (ACA) to effectively allocate and coordinate road resources within groups of CAEVs. By considering the energy consumption and pheromone volatilization, the allocation and coordination process of road resources are optimized. To improve the linear packet loss of RED, we adopt the advanced ACA and CRED in the NS2 platform. The experimental results demonstrate that the proposed method outperforms the RED algorithm in packet loss rate and delay time, significantly enhancing system efficiency and performance. Furthermore, the combination of the CRED algorithm and ant colony algorithm successfully mitigates short-term congestion and identifies optimized paths with minimal delay. |
| first_indexed | 2024-03-11T01:43:00Z |
| format | Article |
| id | doaj.art-7523486e986342e2b7cb444964e18bc6 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T01:43:00Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-7523486e986342e2b7cb444964e18bc62023-11-18T16:26:30ZengMDPI AGElectronics2079-92922023-07-011213299710.3390/electronics12132997Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence ComputingYibo Han0Zheng Zhang1Pu Han2Bo Yuan3Lu Liu4John Panneerselvam5Nanyang Research Institute of Big Data, Nanyang Institute of Technology, Nanyang 473004, ChinaSchool of Computer and Software, Nanyang Institute of Technology, Nanyang 473004, ChinaSchool of Information Engineering, Nanyang Institute of Technology, Nanyang 473004, ChinaDepartment of Informatics, University of Leicester, University Rd, Leicester LE1 7RH, UKDepartment of Informatics, University of Leicester, University Rd, Leicester LE1 7RH, UKDepartment of Informatics, University of Leicester, University Rd, Leicester LE1 7RH, UKThe Internet of Things (IoT) faces significant challenges in the requirements of sensitive task latency, reasonable resource allocation and reliability for resource transactions. This paper introduces a novel method for road resource allocation in the IoT context of connected and autonomous electric vehicles (CAEVs). The proposed algorithm leverages the ant colony algorithm (ACA) to effectively allocate and coordinate road resources within groups of CAEVs. By considering the energy consumption and pheromone volatilization, the allocation and coordination process of road resources are optimized. To improve the linear packet loss of RED, we adopt the advanced ACA and CRED in the NS2 platform. The experimental results demonstrate that the proposed method outperforms the RED algorithm in packet loss rate and delay time, significantly enhancing system efficiency and performance. Furthermore, the combination of the CRED algorithm and ant colony algorithm successfully mitigates short-term congestion and identifies optimized paths with minimal delay.https://www.mdpi.com/2079-9292/12/13/2997ant colony algorithmCAEVsresource allocation |
| spellingShingle | Yibo Han Zheng Zhang Pu Han Bo Yuan Lu Liu John Panneerselvam Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing Electronics ant colony algorithm CAEVs resource allocation |
| title | Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing |
| title_full | Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing |
| title_fullStr | Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing |
| title_full_unstemmed | Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing |
| title_short | Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing |
| title_sort | design and application of a resource allocation method for caevs internet of things based on swarm intelligence computing |
| topic | ant colony algorithm CAEVs resource allocation |
| url | https://www.mdpi.com/2079-9292/12/13/2997 |
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