本文選題：自治車聯(lián)云 + 任務(wù)分配　； 參考：《內(nèi)蒙古大學(xué)》2017年碩士論文

【摘要】：自治車聯(lián)云將分散的、可視為移動(dòng)計(jì)算機(jī)的車輛資源進(jìn)行聚合,像云計(jì)算一樣提供統(tǒng)一資源的按需分配。合理的任務(wù)分配一方面可以使車聯(lián)云中的大量閑置資源得到充分利用,另一方面可以提高任務(wù)的執(zhí)行效率。服務(wù)質(zhì)量問(wèn)題是車聯(lián)云任務(wù)分配研究中的關(guān)鍵問(wèn)題,而時(shí)間指標(biāo)又是服務(wù)質(zhì)量指標(biāo)中的重要指標(biāo)之一。在有時(shí)間指標(biāo)的要求時(shí),任務(wù)承擔(dān)車輛的選擇將影響到有特定時(shí)間要求的任務(wù)成功率。這是由于在高速公路自治車聯(lián)云下,車輛具有高移動(dòng)性,各個(gè)車輛與任務(wù)請(qǐng)求車輛之間的通信鏈路持續(xù)時(shí)間是不同的,而且各個(gè)車輛的運(yùn)算速度也是不同的。所選執(zhí)行任務(wù)車輛的不同,將直接導(dǎo)致有特定時(shí)間要求的任務(wù)的成功率不同。為此,本文提出了一種在高速公路自治車聯(lián)云下滿足服務(wù)質(zhì)量(Quality of Service,QoS)要求的任務(wù)承擔(dān)車輛選擇策略。本策略綜合考慮了車輛之間的通信鏈路持續(xù)時(shí)間以及車輛的運(yùn)算速度等因素,設(shè)計(jì)了任務(wù)承擔(dān)車輛節(jié)點(diǎn)需要重選時(shí)的最優(yōu)選擇方案。最后采用OPNET(Optimized Performance Network Engineering Tools)網(wǎng)絡(luò)仿真平臺(tái)對(duì)提出策略的有效性進(jìn)行了模擬仿真。仿真結(jié)果表明,本文提出的任務(wù)分配策略與隨機(jī)選擇任務(wù)承擔(dān)車輛節(jié)點(diǎn)的策略相比,任務(wù)的成功率提高了 8.7%～10.4%。
[Abstract]:Autonomous vehicle cloud will be dispersed, can be regarded as mobile computer vehicle resources aggregation, like cloud computing to provide a unified allocation of resources according to demand. On the one hand, reasonable task allocation can make full use of a large number of idle resources in the vehicle network, on the other hand, it can improve the efficiency of task execution. The quality of service (QoS) is a key problem in the research of vehicle network task allocation, and the time index is one of the most important indexes in the quality of service (QoS). When there is a time target, the choice of a task bearing vehicle will affect the task success rate with a specific time requirement. This is due to the high mobility of the vehicle under the autonomous vehicle cloud of the freeway, the difference of the communication link duration between each vehicle and the vehicle requesting the task, and the different computing speed of each vehicle. Different vehicles selected to perform tasks will directly lead to different success rates for tasks with specific time requirements. For this reason, this paper proposes a vehicle selection strategy to meet the requirement of quality of Service (QoS) in expressway autonomous vehicle network. This strategy takes into account the communication link duration between vehicles and the speed of the vehicle operation, and designs the optimal selection scheme when the task bearing vehicle nodes need to be reselected. Finally, the effectiveness of the proposed strategy is simulated using OPNET(Optimized Performance Network Engineering Tools) network simulation platform. The simulation results show that the task assignment strategy proposed in this paper increases the success rate of task by 8.7 / 10.4 compared with the strategy of random selection of vehicle nodes.
【學(xué)位授予單位】：內(nèi)蒙古大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U495;TP391.9

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 張春艷;劉清林;孟珂;;基于蟻群優(yōu)化算法的云計(jì)算任務(wù)分配[J];計(jì)算機(jī)應(yīng)用;2012年05期

相關(guān)碩士學(xué)位論文 前4條

1 遲文迪;基于鏈路穩(wěn)定性的車聯(lián)云檢查點(diǎn)服務(wù)器選取方案的研究[D];內(nèi)蒙古大學(xué);2016年

2 范鵬飛;基于自治車聯(lián)云環(huán)境下檢查點(diǎn)服務(wù)器的選取方案的研究[D];內(nèi)蒙古大學(xué);2015年

3 馬晉國(guó);基于車聯(lián)云的協(xié)調(diào)點(diǎn)選擇機(jī)制研究[D];內(nèi)蒙古大學(xué);2014年

4 阮鑫;基于OPNET的無(wú)線Mesh路由協(xié)議分析與仿真[D];西安電子科技大學(xué);2009年

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本文編號(hào)：1883696