An adaptive transmission strategy based on cloud computing in IoV architecture
Abstract Because of recent developments in wireless communication, sensor technology, and computing technology, researchers have recently shown a significant amount of interest in the Internet of Vehicles (IoV), which has become feasible as a result of these improvements. Because of the distinctive...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-03-01
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| Series: | EURASIP Journal on Wireless Communications and Networking |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13638-024-02341-z |
| _version_ | 1797233941083586560 |
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| author | Bin Li Vivian Li Miao Li John Li Jiaqi Yang Bin Li |
| author_facet | Bin Li Vivian Li Miao Li John Li Jiaqi Yang Bin Li |
| author_sort | Bin Li |
| collection | DOAJ |
| description | Abstract Because of recent developments in wireless communication, sensor technology, and computing technology, researchers have recently shown a significant amount of interest in the Internet of Vehicles (IoV), which has become feasible as a result of these improvements. Because of the distinctive characteristics of IoV, such as the varied compute and communication capacities of network nodes, it is difficult to process jobs that are time-sensitive. The purpose of this study is to investigate the ways in which cloud computing may collaborate with the IoV to make the processing of time-sensitive procedures easier. We propose a vehicle design that makes advantage of cloud computing as a means of accomplishing this goal. Increasing the proportion of time-sensitive jobs that are ultimately completed was the motivation behind the development of the offloading model that we devised. Taking this into perspective, we present an adaptive task offloading and transmission method. Taking into account the ever-changing requirements and constraints on the available resources, this algorithm dynamically organizes all of the tasks into separate cloud link lists on the cloud. Following that, the tasks contained within each list are distributed in a cooperative manner to a number of different nodes, with the characteristics of those nodes being taken into consideration. Following the presentation of the simulation model, we carried out an experimental investigation into the effectiveness of the model that was proposed. It is abundantly evident that the proposed model is effective, as indicated by the findings. |
| first_indexed | 2024-04-24T16:24:10Z |
| format | Article |
| id | doaj.art-f9e1c9bb8267484881c2f4a906718b79 |
| institution | Directory Open Access Journal |
| issn | 1687-1499 |
| language | English |
| last_indexed | 2024-04-24T16:24:10Z |
| publishDate | 2024-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Wireless Communications and Networking |
| spelling | doaj.art-f9e1c9bb8267484881c2f4a906718b792024-03-31T11:06:17ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992024-03-012024111810.1186/s13638-024-02341-zAn adaptive transmission strategy based on cloud computing in IoV architectureBin Li0Vivian Li1Miao Li2John Li3Jiaqi Yang4Bin Li5School of Communication and Media, Guangzhou Huashang CollegeFaculty of Science, The University of AucklandSchool of Communication and Media, Guangzhou Huashang CollegeFaculty of Medical and Health Science, The University of AucklandFaculty of Humanities, ZhuHai City PolytechnicFaculty of Humanities, ZhuHai City PolytechnicAbstract Because of recent developments in wireless communication, sensor technology, and computing technology, researchers have recently shown a significant amount of interest in the Internet of Vehicles (IoV), which has become feasible as a result of these improvements. Because of the distinctive characteristics of IoV, such as the varied compute and communication capacities of network nodes, it is difficult to process jobs that are time-sensitive. The purpose of this study is to investigate the ways in which cloud computing may collaborate with the IoV to make the processing of time-sensitive procedures easier. We propose a vehicle design that makes advantage of cloud computing as a means of accomplishing this goal. Increasing the proportion of time-sensitive jobs that are ultimately completed was the motivation behind the development of the offloading model that we devised. Taking this into perspective, we present an adaptive task offloading and transmission method. Taking into account the ever-changing requirements and constraints on the available resources, this algorithm dynamically organizes all of the tasks into separate cloud link lists on the cloud. Following that, the tasks contained within each list are distributed in a cooperative manner to a number of different nodes, with the characteristics of those nodes being taken into consideration. Following the presentation of the simulation model, we carried out an experimental investigation into the effectiveness of the model that was proposed. It is abundantly evident that the proposed model is effective, as indicated by the findings.https://doi.org/10.1186/s13638-024-02341-zCloud computingCloud nodesComputational delayInternet of VehiclesResource utilizationTask offloading |
| spellingShingle | Bin Li Vivian Li Miao Li John Li Jiaqi Yang Bin Li An adaptive transmission strategy based on cloud computing in IoV architecture EURASIP Journal on Wireless Communications and Networking Cloud computing Cloud nodes Computational delay Internet of Vehicles Resource utilization Task offloading |
| title | An adaptive transmission strategy based on cloud computing in IoV architecture |
| title_full | An adaptive transmission strategy based on cloud computing in IoV architecture |
| title_fullStr | An adaptive transmission strategy based on cloud computing in IoV architecture |
| title_full_unstemmed | An adaptive transmission strategy based on cloud computing in IoV architecture |
| title_short | An adaptive transmission strategy based on cloud computing in IoV architecture |
| title_sort | adaptive transmission strategy based on cloud computing in iov architecture |
| topic | Cloud computing Cloud nodes Computational delay Internet of Vehicles Resource utilization Task offloading |
| url | https://doi.org/10.1186/s13638-024-02341-z |
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