車用行動通訊網路中階層式IP分配之動態調整機制

Dynamic Adjustment Mechanism for Hierarchical IP Distribution in VANET

劉德宥(Te-Yu Liu)

指導教授 ： 段裘慶

國立臺北科技大學/電資學院/電腦與通訊研究所/碩士(2011年)

https://doi.org/10.6841/NTUT.2011.00126

摘要

車用行動通訊網路主要面臨挑戰是缺乏基礎設施，且車輛具高速移動能力，因此網路拓樸改變快速，網路規模也較行動隨意示網路(MANET)大。於此種環境中，車輛欲互相交換相關資訊或連結至網際網路前，必須擁有獨一無二的IP位址，且在此高速移動環境下，需較佳的IP位址配置機制，以便透過車載機向路邊之無線存取點(AP)存取網際網路或與其它車輛通訊。
從為數不多的AP環境賦予其配置IP位址之能力，各AP間具階層關聯建構成階層式IP分配機制。當AP耗盡可用IP時，可向上層AP要求資源，使下層AP能繼續配置IP位址給車輛。若上層AP位於交通流量較大之處，又將自身可用IP位址分送，導致資源入不敷出。IP位址之分配與回收均倚賴階層架構，因此AP階層架構建構失當，將導致系統效能降低，且AP頻繁地向上層要求資源，故階層架構建立時，需考慮多方因素，以達到更完善之資源利用。
本研究提出動態調整機制(DAM)，並採基因演算法建構出最佳的AP階層架構，但道路環境為複雜多變且不同的交通流量所對應AP階層架構也不盡相同，即便在系統初期使用基因演算法建立最佳AP階層架構也無法一勞永逸，且在即時性交通資料缺乏情況下搭配灰色理論中灰模型預測交通流量，以適應不同交通環境調整AP階層架構。灰模型可憑藉少數資料進行預測，並視預測結果決定當前AP架構是否再優化調整。
本研究針對IP位址配置以三種評估因子作為評測系統效率之指標，DAM在IP位址平均配置時間(ACT)至少優於HID約25.4%以上；DAM於平均請求次數中(ART)較HID至少改善約3.8%；IP位址平均配置率(AAR)當中，DAM比HID至少提升約4.5%。

關鍵字

車用行動通訊網路 ； IP位址配置 ； 動態調整機制 ； 基因演算法 ； 灰模型

並列摘要

The main challeng of Vehicular Ad-hoc Network (VANET) are both the lack of infrastructure and the high speed mobility of vehicles. As a result, the network topology changes rapidly and the network scale is larger than MANET. In such an environment, for exchanging information over the internet, the vehicles must have an unique IP addresse. Moreover, a better IP address configuration mechanism is required to facilitate devices in the vehicle to access the Internet or communicate with other vehicles via neighbor AP.
Each AP has IP address configuration capabilities from few APs environment, the APs with hierarchical correlation form the hierarchical IP distribution. When an AP runs out of available IPs, it can require IPs from the higher level AP to continue IP addresses assignment. If the higher AP is located in place of heavy traffic, the allocation of available IP addresses may result in resource deficit. The IP address allocation and recycling are based on the hierarchical structure. Hence, improper hierarchical structure of APs may reduce the system performance and AP may frequently request IPs from the higher level APs. Therefore, many factors should be taken into consideration for building the hierarchical structure to achieve better utilization of resources.
Dynamic Adjustment Mechanism (DAM) was proposed to solve aforementioned problems and employed the Genetic Algorithm (GA) to construct a better AP hierarchical structure. However, road environment is complex and real traffic varies over time. The AP hierarchical structure initially constructed by GA cannot be the solution. In case of lacking in traffic data, the grey model based on grey theory could predict the traffic flow in next time. DAM thus could adjust the AP hierarchical structure according to dynamic traffic environment. The grey model prediction based on few data may determine whether the current AP structure should be re-optimized and adjusted according to the prediction results.
In this study, three metrics used to evaluate system performance for IP address configuration. The Average Configuration Time (ACT) is 25.4% lower than HID, the Average Request Times (ART) is 3.8% less than HID, the Average Assignment Rate (AAR) is 4.5% higher than HID.

並列關鍵字

Vehicular Ad hoc Network ； IP addresses configuration ； Dynamic Adjustment Mechanism ； Genetic Algorithm ； Grey model

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