臺灣博碩士論文加值系統

現在繞徑協定再車載行動隨意網路吸引很多的注意，大部分的研究強調最小化點對點延遲且並沒有注意在減少無線資源的使用上。此篇論文注重在限制延遲繞徑，目標在傳遞訊息到目的地在使用者限制的延遲時間內且最小化無線資源使用率。訊息可以被傳遞到目的地經由混合的方式在經由車子攜帶或無線傳輸。在現存的協定上，車子只有交換傳送策略在十字路口時，根據可用的分配時間在下一個路段上。為了增強之前的研究，我們的協定使用線性回歸來預測可用時間經由移動的距離，如此車子就可以交替合適的傳遞方式在合適的時間。所以我們的協定可以減少頻率在資料傳遞且減少無線資源使用率。我們的協定包含兩個策略，本地的方式和集中的策略。本地的策略只使用車子本身的速度來預測可用的時間且決定何時交換傳遞方式。集中式的策略使用統計的資訊來做決定。模擬結果顯示我們的協定效果比教好比現存的協定。

Routing protocols for vehicular ad hoc networks (VANETs) have attracted a lot of attentions recently. Most of the researches emphasize on minimizing the end-to-end delay without paying attention to reduce the usage of radio. This paper focuses on bounded delay routing, whose goal is to deliver messages to the destination within user-defined delay and minimize the usage of radio. The messages can be delivered to the destination by the hybrid of data muling (carried by the vehicle) and forwarding (transmitted through radio). In the existing protocol, a vehicle may only switch the delivery way (muling or forwarding) at an intersection according to the available time of the next block. To improve previous works, our protocol uses linear regression to predict the available time and the traveling distance and thus the vehicle can switch to a proper delivery way at a proper moment. Therefore, our protocol can reduce the frequency of data forwarding and thus reduces the usage of radio. Our protocol contains two schemes: the localized and centralized schemes. The localized scheme uses only the local vehicle's speed to predict the available time and to decide when to switch the delivery way; while the centralized scheme uses the global statistical information to make the decision. Simulation results show that our protocol performs better than the existing protocol.

1 Introduction 1
2 Related Works 4
3 Preliminary 7
3.1 SystemModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.2 Basic Idea and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
4 Delay-Bounded Routing Protocol with Linear Regression 12
4.1 Reducing Control Packet Size . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4.2 Delay-Bounded Greedy Forwarding with Linear Regression (LR-Greedy) . . . 14
4.3 Delay-Bounded Centralized Forwarding with Linear Regression (LR-Centralized) 18
5 Simulation results 24
5.1 Delivery Ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
5.2 Transmitted Bytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
5.3 Average Delivery Delay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.4 Resvering time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
6 Conclusions

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