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隨意網路中以價格機制為基礎之效率路徑選擇演算法 / Efficient Routing Path Selection Algorithm based on Pricing Mechanism in Ad Hoc Networks林建圻 Unknown Date (has links)
隨著行動通訊技術日漸進步,隨意網路具備不需要事先建設基礎設施、使用者可以自由移動等特性,未來將很有發展潛力。隨意網路亦具有多跳接的特性,通常都必須由別人幫忙轉送封包到達目的地端。想要使隨意網路能夠普及化,必須提供一個良好的動機,讓隨意網路中的使用者彼此互相合作,願意互相幫忙轉送封包。我們根據參考的論文所提出來的虛擬貨幣交易網路,分析網路資源數量與價錢的關係,提出了一個合理的定價機制。同時也結合隨意網路移動的特性,讓使用者選擇效率較高的路由來傳遞封包。最後我們提出了一個簡單的路由協議,結合了價格機制,而能應用於隨意網路中。實驗結果顯示我們的路由協議能夠提昇整體的網路效能。使用此價格機制結合我們提出的路由協議對使用者而言也是最具經濟效益的。 / In military and rescue applications of mobile ad hoc networks, all the nodes belong to the same authority. Therefore, they are motivated to cooperate in order to support the basic functions of the network. However, the nodes are not willing to forward packets for the benefits of other nodes in civilian applications on mobile ad hoc networks. In view of this, we adopt the “pay for service” model of cooperation, and propose a pricing mechanism combined with routing protocol. The scheme considers users’ benefits and interference effect in wireless networks, and can distribute traffic load more evenly to improve network performance. The simulation results show that our algorithm outperforms other routing protocols. Using our pricing mechanism and routing protocol at the same time can achieve more economical efficiency.
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在MANET中基於社群關係導向之傳輸機制研究 / A social relationship based transmission scheme in MANET李佩璇, Lee, Pei Hsuan Unknown Date (has links)
資訊世代的來臨,手機、筆記型電腦、iPod、iPad不勝枚舉的手持行動裝置充斥在我們的生活周遭。這些裝置上都擁有一種以上的無線網路介面,例如:紅外線、藍芽、WiFi,及行動網路介面等。由於手持裝置的盛行,構成行動隨意網路(Mobile Ad Hoc Network)的傳輸空間越來越普遍,伴隨而來的問題如節點可能任意移動,拓樸不斷改變等,造成傳輸中斷。而在有網路的環境下如何從較信任的人(節點)獲取較可信任的資訊,將是重要的議題。因此本論文導入目前炙手可熱與我們生活密不可分的社群網路(social network),利用社會網路分析(social network analysis)將人與人之間關係數據化,做為轉傳依據。我們提出Ego-Centric Social Network Routing中繼節點 (relay node) 選擇的策略,簡稱ECSNR。除了利用社會網路分析的方法外也加入候選清單,使負載過重的節點直接由清單中之候選節點協助轉傳、推薦清單,讓路由中繼的位置更靠近負載過重之節點,加速訊息的傳遞,也可藉由緊密度高且較可信任之節點協助傳送。另外當訊息無法藉由社會網路輔助(social networking aided)傳輸時,便會利用興趣導向(interest-based)傳輸,依照節點興趣相似性判別興趣區間,將訊息傳遞出去。最後,由實驗模擬結果得知,當網路節點數量增加時,封包送達率能有7.4%~15.8%的改善。End to end delay有10%~15.2%的改善;control overhead雖然較遜色,但依然平均控制在9.4%內。Average hop count平均減少1.7 個hops數。網路移動速度比較的實驗中,封包送達率能有8%~24.2%的改善;control overhead雖然較遜色,但依然平均控制在8.8%內。End to end delay有約4.7%~15.2%的改善;average hop count平均減少2.4個hops數。 / With the coming of information era, our lives have been filled with varied mobile devices, such as cell phones, notebooks, iPods, and iPads. All these devices are equipped with more than one wireless network interface, including Infrared, Bluetooth, WiFi, mobile network interface etc. Due to the popularity of mobile devices, Mobile Ad Hoc Networks have been more widespread than ever. However, movable nodes and the constantly changing topology could cause transmission interruption. Therefore, “how to obtain trustworthy information from trusty nodes” is a significant issue.
This thesis geared toward the social network which is inseparable from our lives at this moment. In this thesis, social network analysis is employed, and the relationship data is used as the base of relay. We propose a relay-node selection strategy of Ego-Centric Social Network Routing (ECSNR), and apply the method of using candidate list. All these can be used to speed up the transmission process. Because the candidate nodes are the closest ones to the overloaded nodes, the relay process can be more efficient and speedy. The transmission can also be done through the stable and trustworthy nodes. When a message can not be transmitted through the social network aided nodes, the interest based nodes can help to transmit according to the interest similarity.
The results of experiment simulations show that along with the increase of network nodes, the packet delivery ratio can be improved by 7.4% ~ 15.8%. The end to end delay can be improved by 10% ~ 15.2%, and the average control overhead is within 9.4%. The average hop count can be reduced by 1.7 hops. Given the nodes are moving, the packet delivery ratio can be improved by 8%~24.2%, and the average control overhead is within 8.8%. The end to end delay can be improved by 4.7% ~ 15.2%, and the average hop count can be reduced by 2.4 hops.
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