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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/101439

    Title: 適用於ZigBee物聯網生成與資料收集協定之研究
    Other Titles: Research on Formation and Data Collection Protocols for Zigbee Machine to Machine Networks
    Authors: 潘孟鉉
    Contributors: 淡江大學資訊工程學系
    Keywords: 資料收集技術;物聯網;網路生成;路由協定;時槽分派;ZigBee;convergecast;machine-to-machine networks;network formation;routing protocol;slot assignment;ZigBee
    Date: 2012-08
    Issue Date: 2015-04-29 16:47:01 (UTC+8)
    Abstract: 近年來ZigBee通訊技術被廣泛的提及用於「物聯網」系統中,物聯網是一個概念性名詞其主要目的是要將所有物品透過感測設備與網際網路連接起來並提供智慧化服務,如智慧型大眾運輸系統、生態環境監控、公共與居家安全防護等。本計畫擬研究以ZigBee為基礎之物聯網路生成與資料收集通訊協定,我們假想一個ZigBee物聯網路架構為一階層式架構(Hierarchical),在此場景中有一骨幹網路,該骨幹網路用以連接所有的子網路們,基於此架構,本計畫分為三個研究主題分述如下: 在第一個研究主題中,我們將研究該如何生成一個以ZigBee節點所組成的骨幹網路,並討論為何ZigBee規範並不適用於自動生成一個大型網路,本研究主題的目標為設計一網路生成方式用以自動生成一個大型骨幹網路,我們預計設計具有類似ZigBee分散式演算法特性的位址指派方式,且該位址指派方式亦可以支援Stateless路由方法,然而節點依然可以儲存少許的路由資訊來加速封包之傳遞,縮短封包在網路間的跳躍次數並減少路由負擔。 第二個研究主題考量在子網路中只有單一資料收集閘道器的網路場景,並且提出具有低功耗低延遲特性的網路生成與資料收集通訊協定,我們使用ZigBee所定義之Superframe架構來達到低功耗之目的,並且藉由安排時槽的方式來實現低傳輸延遲。我們提出新的時槽干擾鄰居之定義,該定義能限縮干擾鄰居之數量,並且搭配提出重連結裝置演算法,該演算法可以基於新的干擾鄰居之定義來消弭有可能之干擾鄰居之數量,並且使得在安排時槽時能更有效率,更能降低回報延遲。 第三個研究主題我們擴展第二個研究主題,並且讓子網路中能有多個資料收集閘道器,此研究主題之目的為讓所設計的網路能夠支援多樣化的回報內容。我們將設計一個網路生成方式來找到最佳網路拓樸,該網路拓樸可以使得網路上的節點醒來運作的次數最少,便得以回報數值到各個資料收中心。接著我們亦提出降低回報延遲的時槽分配方法,我們將調整ZigBee 訊框架構,並且依照網路拓樸的特性來分派路由器所該使用的時槽,藉此來達到低回報延遲之目的。 我們相信上述的三個研究方向可以涵蓋大部分ZigBee物聯網路對於通訊與網路架構上的需求,除了理論方面的探討外,本計畫也預計實做所設計之演算法,我們期許本計畫能夠理論與實務兼顧,並且成為ZigBee物聯網路的尖端研究。
    Recently, ZigBee protocol is well discussed in machine-to-machine networks (M2M network). The M2M network is a network type, which aims to connect all objects or goods by sensors or the Internet. It can provide various kinds of services like intelligent transportation system (ITS), environment monitoring, public/home security services, and so on. In this project, we would like to investigate ZigBee based machine-to-machine network formation and convergecast protocols. We assume a ZigBee hierarchical network as a M2M network. In this network, there are some backbone nodes to form a backbone network. These backbone nodes can connect all sub-networks, which are also formed by ZigBee nodes. This project contains three research topics as describe below. In the first research topic, we will investigate how to organize ZigBee nodes to form a M2M backbone network. We discuss why the proposed ZigBee specification cannot be used to form such a large scale network. The goal is to design a network formation algorithm to automatically form a M2M backbone network. We will design a ZigBee-like distributed address assignment scheme. The address assignment can support stateless routing protocol. Network nodes may save some routing information to enhance packet transmissions. The routing information can reduce hop distances between nodes and routing overhead. The second research topic considers the sub-network environment with only one sink. We plan to design network formation and convergecast protocols. We use the ZigBee superframe structure to support low power operation in the network. And we carefully assign active slots to nodes to reduce the report latency. We propose new definition of interference neighbors when assigning active slots. Compare to previous works, this new definition can help to further reduce the number of interference numbers. We will design a node re-connecting protocol to eliminate potential interference neighbors. As a result, we can have a better slot assignment to further reduce report latency. The third research topic extends the second one to consider there are multi-sinks in the sub-network environment to support various kinds of report types. We will design a network formation protocol to find the best network topology, which can minimize the wake-up times of nodes. We guarantee that all readings can report to sinks under the wake-up schedule. We will also design slot assignment scheme to reduce the report latency in this environment. The strategy is to modify the ZigBee superframe structure to let a node use multiple active slots. When assigning slots, the algorithm also takes network topologies into consideration. We believe the above three topics can cover most needs on topologies and communication of ZigBee M2M networks. We will not only do researches, but also implement our designed algorithms. We will also discuss the differences between simulations and prototyping experiences. We consider that we can be pioneers in the field of ZigBee M2M networks.
    Appears in Collections:[資訊工程學系暨研究所] 研究報告

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