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移動(dòng)邊緣計算環(huán)境下基于改進(jìn)GPSR的VANET路由算法
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川北幼兒師范高等專(zhuān)科學(xué)校

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河南省科技廳科技攻關(guān)計劃項目(202002210346)


VANET Routing Algorithm Using Improved GPSR and Adaptive Link Quality Assessment
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    摘要:

    針對車(chē)輛自組織網(wǎng)絡(luò )(Vehicular Ad-Hoc Network,VANET)中現有路由協(xié)議存在的路由選擇錯誤、丟包率較高、服務(wù)質(zhì)量低等問(wèn)題,提出了移動(dòng)邊緣計算環(huán)境下,結合改進(jìn)貪婪周邊無(wú)狀態(tài)路由(Greedy Perimeter Stateless Routing,GPSR)和自適應鏈路質(zhì)量評估的VANET路由算法。首先,結合邊緣計算構建了VANET通信模型,對其車(chē)輛位置和速度進(jìn)行系統的理論分析。將邊緣計算架構應用于VANET能夠有效緩解計算量大、與車(chē)輛有限且不均的資源分布之間的矛盾。然后,提出了基于節點(diǎn)移動(dòng)速度和節點(diǎn)間距離的改進(jìn)GPSR協(xié)議,通過(guò)自適應鏈路穩定性和鏈路傳遞速率評估來(lái)選擇合適的中繼節點(diǎn),動(dòng)態(tài)更新鏈路。通過(guò)SUMO仿真平臺對路由算法的性能進(jìn)行評估,實(shí)驗結果表明,相對于其他算法,所提算法受車(chē)輛密度、交通流以及車(chē)輛相對速度的影響較小,且提高了分組傳送率(車(chē)輛數為300時(shí)傳送率達到92%),減少端到端延遲(交通流為5時(shí)延遲降低到1.5s),從而降低了通信開(kāi)銷(xiāo)。

    Abstract:

    Aiming at the problems of the existing routing protocols in vehicular ad hoc network (VANET), such as wrong routing, high packet loss rate and low quality of service, this paper proposes a VANET routing algorithm in the mobile edge computing environment, which combines the improved greedy perimeter stateless routing (GPSR) and adaptive link quality assessment. First of all, combined with edge computing, the VANET communication model is constructed, and the vehicle position and speed are analyzed systematically. The application of edge computing architecture in VANET can effectively alleviate the contradiction between large amount of computing and limited and uneven distribution of resources. Then, an improved GPSR protocol based on the mobile speed of nodes and the distance between nodes is proposed. Through the adaptive link stability and link transfer rate evaluation, the appropriate relay nodes are selected and the link is dynamically updated. The performance of the routing algorithm is evaluated by SUMO simulation platform. The experimental results show that compared with other algorithms, the proposed algorithm is less affected by vehicle density, traffic flow and vehicle relative speed, and improves packet transmission rate (92% when the number of vehicles is 300), reduces end-to-end delay (1.5s when the traffic flow is 5), thus reducing the communication cost.

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陳登,潘力.移動(dòng)邊緣計算環(huán)境下基于改進(jìn)GPSR的VANET路由算法計算機測量與控制[J].,2022,30(1):188-195.

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歷史
  • 收稿日期:2021-07-08
  • 最后修改日期:2021-07-22
  • 錄用日期:2021-07-22
  • 在線(xiàn)發(fā)布日期: 2022-01-24
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