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Author: 郭心傑
Enrico - Winata
Thesis Title: 適用於RFID標籤辨識的八位式反碰撞演算法
Octad Algorithm for RFID Tag Identification
Advisor: 羅乃維
Nai-Wei Lo
Committee: 徐俊傑
Chiun-Chieh Hsu
Yuan-Cheng Lai
Degree: 碩士
Department: 管理學院 - 資訊管理系
Department of Information Management
Thesis Publication Year: 2010
Graduation Academic Year: 98
Language: 英文
Pages: 50
Keywords (in Chinese): 無線射頻辨識反碰撞標籤碰撞標籤辨識樹架構演算法
Keywords (in other languages): tree-based
Reference times: Clicks: 68Downloads: 2
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  • 無線射頻辨識(RFID)一種非接觸式的識別技術,擁有高速辨識的能力。在最近幾年來,RFID已被廣泛的應用,從供應鏈關理系統、高速公路電子收費系統、醫療保鍵等等。RFID的讀取器擁有迅速的讀取標籤的能力,但是由於讀取器與標籤之間的通訊使用了相同的頻道,當多個標記同時傳送他們的識別至讀取器時,它們所傳送的訊號將互相碰撞變成了雜訊並且無法被讀取器辨識,造成了讀取時間的延遲以及能源上的浪費。因此,為了解決訊號碰撞的問題以提高RFID的讀取效能,反碰撞演算法是必須存在的。在此本論文中,我們提出了基於樹狀架構的新反碰撞演算法,稱為八位式反碰撞演算法(Octad)。八位式反碰撞演算法使用了二個新的概念:三位元檢查字串及三位元加密字串以製作標籤回應訊息的規則與元件。根據模擬的結果顯示,八位式反碰撞演算法所改善的延遲時間及能源浪費勝過其他現有的基於樹狀架構的的反撞演算法。

    Radio Frequency IDentification (RFID), a non-contact identification technology, which has high speed identification ability, is widely implemented in several applications, such as supply-chain management systems, Electronic Toll Collection, healthcare facilities, etc. The concept of RFID is to use the reader to gather the information from the tags as quickly as it can. The communication between the reader and the tags uses a shared wireless channel. When multiple tags simultaneously transmit their IDs back to the reader, signal collision will occur, increases the higher transmission delay and communication overhead. Thus, it is urgently needed a signal collision resolution for efficient tag identification. In this paper, we propose a novel, tree-based anti-collision scheme, called The Octad Algorithm (Octad) which embeds two novel concepts, i.e. 3-bit parity string and 3-bit encoding string. The simulation results show that Octad outperforms other existing tree-based anti-collision schemes in terms of identification delay and communication overhead.

    Chapter 1. INTRODUCTION 1 Chapter 2. RELATED WORK 5 2.1. Query Tree 8 2.2. Binary Search 10 2.3. Variation of Query Tree 13 2.4. Improved Binary Search 14 Chapter 3. OCTAD ALGORITHM 16 3.1. The procedure of Octad algorithm 19 3.2. An Example 24 Chapter 4. PERFORMANCE COMPARISON 29 4.1. The impact of the Number of Tags 30 4.2. Impact of the density 34 4.3. Impact of the Length of Tags IDs 39 Chapter 5. CONCLUSION 40 Chapter 6. REFERENCE 41

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