研究生: |
江東鴻 Tung-Hung Chiang |
---|---|
論文名稱: |
於感測網路中考量獨立節點且具區域能源感知的叢集機制之研究 Study on Regional Energy Aware Clustering with Isolated Nodes in Wireless Sensor Networks |
指導教授: |
呂政修
Jenq-Shiou Leu |
口試委員: |
陳省隆
Hsing-Lung Chen 孫敏德 Min-Te Sun 石維寬 Wei-Kuan Shih |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電子工程系 Department of Electronic and Computer Engineering |
論文出版年: | 2014 |
畢業學年度: | 102 |
語文別: | 英文 |
論文頁數: | 31 |
中文關鍵詞: | 能源感知叢集 、能源消耗 、分散式分群演算法 、獨立節點 |
外文關鍵詞: | Energy Aware Clustering, Energy Consumption, Distributed Clustering, Isolated Nodes |
相關次數: | 點閱:426 下載:3 |
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在無線感測網路中,受限於感測器的有限資源,如何在有限的能源下提高網路的效能,是無線感測網路中很重要的議題。雖然利用叢集架構能夠有效減少資料傳輸次數以達到節省能源的效果,但在建構叢集以及選取叢集首(cluster-head)的過程中也會造成許多額外的能源消耗。本研究提出一個新的叢集演算法(Regional Energy Aware Clustering with Isolated Nodes,REAC-IN),利用前一回合各叢集的平均剩餘能源做為下一回合選取叢集首的基準,讓各個區域剩餘能源較高的節點能夠擁有競爭叢集首的資格。因此,我們提出的方法能夠有效的保護在大多分散式叢集架構機制中所產生出來的獨立節點(Isolated Nodes),利用平均剩餘能源以及節點與伺服端(Sink)的距離來決定是否獨自傳送資料到伺服端或是傳送資料到上一輪的叢集首,使得整體網路能達到平衡的能源消耗。最後在網路模擬器(Network Simulator version 2,NS-2)上的模擬結果顯示在整體網路效能上,本研究所提出的演算法比分散式叢集演算法(Distributed Energy Efficient Clustering,DEEC)以及許多傳統的叢集演算法來的更有效率。
Energy consumption is a critical concern in the design of wireless sensor networks (WSNs), which are typically powered by limited energy resources. A suitable clustering algorithm for grouping sensor nodes can increase the energy efficiency of WSNs. However, clustering requires additional overhead, such as cluster head (CH) selection and assignment and cluster construction. This paper proposes a new regional energy aware clustering method using isolated nodes for WSNs, called Regional Energy Aware Clustering with Isolated Nodes (REAC-IN). In REAC-IN, CHs are selected based on weight. Weight is determined according to the residual energy of each sensor and the regional average energy of all sensors in each cluster. Improperly designed distributed clustering algorithms can cause nodes to become isolated from CHs. Such isolated nodes communicate with the sink by consuming an excess amount of energy. To reduce energy consumption and prolong network lifetime, the regional average energy and the distance between sensors and the sink are used to determine whether the isolated node sent its data to a CH node in the previous round or to the sink. The simulation results of the current study revealed that REAC-IN outperforms other clustering algorithms, namely the LEACH, HEED, and DEEC algorithms, in the total number of transferred data, total network energy consumption, and network lifetime.
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