資料收集是在許多無線感測器網絡應用中的基礎工作。為了節省感測器之電量，許多先前的無線感測器網路的研究討論如何排程傳輸連結上之節點睡醒時機(或稱時槽)。為了節省資料延遲，傳輸連結所使用之時槽必須小心的指派。近年來，多頻道的概念被提出可應用於指派時槽的方法中。當網絡中有多個可用頻道時，可使得傳輸對之間的干擾可被消除，因此亦可更進一步地降低資料回報延遲。在本篇論文中，我們將上述的場景定義為一最小延遲排程問題(minimal delay scheduling problem)，並證明此問題為一 NP-complete問題，我們提出了一個包含三階段的演算法。在前兩階段中，我們的目標是盡可能減少資料回報之延遲，我們透過觀察網絡拓樸及各種不同的指派策略之方式來設計我們的演算法。而在第三階段中，我們的目標是消除傳輸連接間的干擾，並仔細調整前一階段所指派之時槽。透過模擬和實作結果，我們發現我們所設計之演算法能有效地降低多頻道無線感測器網絡之資料收集延遲。

Convergecast is a fundamental operation in many wireless sensor network (WSN) applications. To conserve energy, many previous WSN protocols discuss to periodically schedule active timings (or say slots) of transmission links in the network. When collecting data, the slots should be carefully assigned to conserve latency. Recently, the multichannel concept is utilized to facilitate slot assignment. When the network has multiple channels, the convergecast latency can be further reduced since the interferences between transmission links can be eliminated .In this work, we model the above scenario as a minimal delay scheduling (MDS) problem, and prove it as an NP-complete problem. We propose a heuristic algorithm, which contains three phases. In the first two phases, we aim to minimize the report latency as possible as we can. Our designs are based on several observations on the shape of the network and on the assignment strategies. Then, in the third phase, we aim to eliminate interferences between links, and carefully adjust some slots if necessary. Simulation and implementation results indicate that the proposed scheme can effectively reduce the convergecast latency in WSNs with multiple channels.

Contents
Chapter 1 Introduction  1
Chapter 2 Related works 5
Chapter 3 Network models  8
Chapter 4 The proposed scheme  12
4.1 The Tree Formation Phase 12
4.2 The Slot Assignment Phase 15
4.3 The Channel Assignment Phase  20
Chapter 5 Simulation Results 26
Chapter 6 Implementation Results  30
Chapter 7 Conclusions  33
Bibliography  34
Appendix  36
附錄 38

List of Figures
Figure 1.1: The network scenario. 3
Figure 3.1: Interference relationships.  9
Figure 4.1: An example of the step 3 in the proposed tree formation phase. 14
Figure 4.2: An example of the step 3 of the proposed slot assignment scheme.  16
Figure 4.3: A slot assignment result of the complete tree with parameters Dg and Dp. 17
Figure 4.4: The relationship between i and nodes in PI(i). 21
Figure 5.1: Simulation results on the effects of network size when there are (a) unlimited and (b) limited number of channels. 27
Figure 5.2: Simulation results on the effects of (a) network density and (b)transmission ranges of nodes. 28
Figure 5.3: Simulation results on the effects of the number of channels. 29
Figure 6.1: The tree topology and slot and channel assignment results of our implementation.  32
Figure 6.2: Experiment results of OUR and CF. 32

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