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研究生:高宗毅
研究生(外文):Tsung-Yi Kao
論文名稱:基於Fuzzy C-Means聚類法之混合型階層式群集方法於無線感測網路之研究
論文名稱(外文):A Hybrid Hierarchical Clustering Approach Based on Fuzzy C-Means for Wireless Sensor Networks
指導教授:李俊賢李俊賢引用關係
口試委員:許佳興李岳峰高立人
口試日期:2012-07-31
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電機工程系研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:65
中文關鍵詞:無線感測網路階層式演算法群集方法群集簇頭能源消耗
外文關鍵詞:Wireless sensor networkhierarchical routing algorithmcluster headclustering approachesfuzzy c-meansenergy consumption
相關次數:
  • 被引用被引用:0
  • 點閱點閱:180
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  • 下載下載:7
  • 收藏至我的研究室書目清單書目收藏:0
近年來,由於半導體的發展,帶起無線感測網路(wireless sensor network, WSN)的進步。在無線感測網路中,感測節點通常佈置於不易維護的環境,以及感測節點能源上的限制。因此學者們為了提高節點能源使用效率,提出各種路由演算法,依結構可分成平面式、階層式、基於位置三種。其中階層式演算法可再區分為分散式與集中式演算法,其中最具代表性的分散式演算法為低能源自適應性群集階層式路由演算法(low energy adaptive clustering hierarchy, LEACH)。它是由隨機選擇群集簇頭(cluster head, CH),以及輪流當任CH的方式,使感測節點之能源均勻使用,有效的提升網路壽命。而集中式演算法是透過基地台(base station, BS)做分群,典型的演算法如LEACH-Centralized (LEACH-C)。
本論文是以LEACH演算法為基礎來改良,提出混合型階層式群集方法(hybrid hierarchical clustering approach, HHCA),將分群演算法之結構進一步拆分成上、下層兩個部份。在上層方面,我們使用集中式的方式執行Fuzzy C-Means聚類法計算上層分格(grid)。在下層方面,以分散式的LEACH加入感測節點能源與節點數量之考量,進一步對grid再做分群。利用由上往下的選擇順序,及混合分散式與集中式的選擇方式,達到分群再分群的階層式結構,以延長感測網路的壽命。


In recent years, because of development of the semiconductor technology, it leads the progress of wireless sensor networks (WSNs). In WSNs, sensor nodes are usually arranged in a hardly maintainable environment and sensor nodes have limited on energy. Thus, scholars have proposed routing algorithms in order to improve energy efficiency. Routing algorithms in WSNs can be divided into flat-based routing, hierarchical-based routing, and location-based routing depending on the network structure. Hierarchical-based routing can be further divided into the distributed and centralized routing algorithms. Low energy adaptive clustering hierarchy (LEACH) is the most representative distributed routing algorithm. LEACH uses random rotation mechanism to select cluster head (CH) to improve WSN lifetime. LEACH-Centralized (LEACH-C) is a centralized routing algorithm and it selects CH by base station (BS).
In this paper, based on the LEACH, we proposed hybrid hierarchical clustering approach (HHCA). The approach is split into upper and lower layer according to the algorithm structure. First, we use Fuzzy C-Means clustering method to calculate the grid head by BS in the upper layer. Then, based on the LEACH, we consider remaining energy and number of nodes to cut the grid in the lower layer. By different selection order, mixed selection mechanism lead to a hierarchical structure and improve WSN lifetime.


摘 要 i
ABSTRACT ii
誌 謝 iii
目 錄 iv
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 1
1.3 研究方法 2
1.4 研究貢獻 3
1.5 論文架構 3
第二章 無線感測網路之相關技術 4
2.1 無線感測網路基礎架構 4
2.2 減緩信號干擾影響與封包碰撞預防技術 5
2.2.1 直接串列擴頻(DSSS) 5
2.2.2 載波偵測多重存取(CSMA) 5
2.2.3 多工存取技術(Multiple Access) 6
2.3 無線傳輸之路徑損失特性 7
2.4 資料融合技術(Data Aggregation) 7
第三章 路由演算法相關研究 8
3.1 路由演算法簡介 8
3.2 階層式路由演算法 9
3.2.1 雙層式路由演算法 9
3.2.2 三層式路由演算法 20
第四章 聚類演算法 25
4.1 聚類演算法介紹 25
4.1.1 K-Means聚類法 25
4.1.2 Fuzzy C-Means聚類法 27
第五章 混合型階層式群集方法(HHCA) 29
5.1 一階無線廣播模型(First Order Radio Model) 29
5.2 演算法架構敘述 30
5.3 設定狀態(Set-Up State) 33
5.3.1 設定狀態流程 33
5.4 穩定狀態(Steady State) 39
5.4.1 各種節點之穩定狀態流程 40
5.4.2 穩定狀態流程 42
5.5 系統結構比較與特徵 44
第六章 模擬結果與分析 46
6.1 實驗規劃 46
6.2 HHCA之參數分析 47
6.3 HHCA之性能評估 47
6.3.1 隨機均勻分佈(Uniform Distribution) 48
6.3.2 隨機常態分佈(Normal Distribution) 54
第七章 結論與未來工作 58
7.1 結論 58
7.2 未來工作 59
參考文獻 61


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