| Autor: |
Peng QIN, Haoting HE, Xiongwen ZHAO, Yang FU, Yu ZHANG, Miao WANG, Shuo WANG, Xue WU |
| Jazyk: |
čínština |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Tongxin xuebao, Vol 43, Pp 113-125 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1000-436X |
| DOI: |
10.11959/j.issn.1000-436x.2022129 |
| Popis: |
In order to reduce the number of road side unit (RSU) and meet the needs of mobile vehicle users for processing latency-sensitive and computation-intensive tasks, a context-aware resource allocation algorithm was proposed based on parked cars.Road side parked vehicles were selected to serve the vehicle users instead of RSU using parking time as a factor for determining whether a parked vehicle could become a parked car roadside unit (PCRSU).In order to further reduce the system response time, a mechanism was designed considering content caching and distribution.In respect to user content caching, PCRSU made personalized content recommendation for vehicle users with awareness by using two elements of user historical search data and point of interest (PoI) area type.In respect to content distribution, PCRSU allocated bandwidth efficiently by sensing the data transmission needs of vehicle users.Extensive experiments show that compared with the existing benchmark methods, the proposed algorithm can select PCRSU more reasonably, effectively reduce the demand response delay, improve the stability of the network while ensuring network coverage, and provide more accurate service content for vehicle users. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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