在無線感測網路中採用叢集（cluster）機制能減少能源消耗，延長網路生命週期（network lifetime）並改善可擴充性。在一個典型的叢集式感測網路中，感測節點會被組織為叢集。每個叢集推舉一個叢集頭（cluster head）。叢集頭負責幫叢集成員收集感測的資料，執行資料聚集並藉由多跳躍路徑（multi-hop path）方式透過中繼的叢集頭將資料送達目的端節點。以此方式，採取叢集技術不但縮短傳送距離並且降低能源消耗；然而，在每個叢集中之叢集頭的流量負擔勢必加重。在此情境下，接近目的端節點之叢集頭必定快速地將自身的電力耗盡。為了克服此問題，我們試圖從兩個方面著手進行能源平衡之議題。
在第一個研究主題中，首先我們針對無線感測網路之日冕模型（corona model）進行分析。基於分析之結果，我們發現預先安排不同的初始情境將可實現近似能量平衡之無線感測網路。隨後我們提出Energy-balanced Node Deployment with Balanced Energy（END-BE）機制與Energy-balanced Node Deployment with Maximum Life-Time（END-MLT）機制，依據每個叢集頭之能量消耗來決定每層日冕中之叢集節點密度。模擬結果顯示，採用END-BE機制將可達到近似平衡之能量消耗，採用END-MLT機制將可顯著提昇網路生命週期。
在第二個研究主題中，我們針對日冕結構之無線感測網路發展一套新穎的叢集式路由協定。依據每個叢集頭負擔之網路流量，藉由近似能量消耗平衡之數學分析來決定適當的半徑。模擬結果證實，與Multi-Layer Clustering Routing Algorithm（MLCRA）相比，我們的機制有效地改善網路生命週期、剩餘電量與減少叢集頭轉移次數。

Clustering schemes can reduce energy consumption, prolong network lifetime and improve scalability in wireless sensor networks (WSNs). In a typical cluster-based WSN, sensor nodes are organized into clusters. Each cluster elects a cluster head (CH) node. The CH is responsible for collecting the sensed data from cluster members, aggregating data and transmitting data to the sink node via a multi-hop path through intermediate CHs. Thus, the use of cluster techniques not only shortens the transmission distances for sensor nodes but also reduces energy consumption; however, each cluster imposes a larger load on the CH. Under this situation, CHs closer to the sink node tend to use up their batteries faster than those farther away from the sink node due to imbalanced traffics among CHs. To overcome this problem, we contribute to the energy balancing issues in WSNs from two aspects.
In the first work, we first analyze the corona model. Based on analysis results, we found that nearly balanced energy consumption of WSNs can be achieved with the additional help of arranging different initial conditions. We then propose the Energy-balanced Node Deployment with Balanced Energy (END-BE) scheme and Energy-balanced Node Deployment with Maximum Life-Time (END-MLT) scheme, which determine the cluster density for each corona according to the energy consumption of each CH. Simulation results show that energy consumption is nearly balanced by implementing END-BE, and the network lifetime is greatly improved by adopting END-MLT.
In the second work, we development a novel cluster-based routing protocol for corona-structured wireless sensor networks in order to balance the energy consumption among CHs. Based on the relaying traffic of each CH conveys, adequate radius for each corona can be determined through nearly balanced energy depletion analysis, which leads to balanced energy consumption among CHs. Simulation results demonstrate that our clustering approach effectively improves the network lifetime, residual energy and reduces the number of CH rotations in comparison with the Multi-Layer Clustering Routing Algorithm (MLCRA).

論文審定書 (in Chinese) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
論文審定書 (in English) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Abstract (in Chinese) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
Abstract (in English) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Contributions of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Organization of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2 Overviews of Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1 Flat Routing Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.2 Location-based Routing Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3 Hierarchical Routing Protocol . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.4 Other Energy-efficient Issues in WSNs . . . . . . . . . . . . . . . . . . . . . . . . 28
2.5 Arranging Cluster sizes and Transmission ranges for WSNs . . . . . . . . 31
2.5.1 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.5.2 Network Initialization Phase . . . . . . . . . . . . . . . . . . . . . . . . 33
2.5.3 Cluster Establishment Phase . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.5.4 Data Transmission Phase. . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
2.5.5 Cluster Maintenance Phase . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.5.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3 Novel Node Deployment Strategies in Corona Structure for WSNs . . . 47
3.1 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.1.1 Assumptions and Network Models . . . . . . . . . . . . . . . . . . . . 47
3.1.2 Definitions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.2 Analysis of the Corona Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.2.1 Energy Consumption Analysis . . . . . . . . . . . . . . . . . . . . . . . 52
3.2.2 Balanced Energy Consumption. . . . . . . . . . . . . . . . . . . . . . . 54
3.3 Network Initialization Phase. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.3.1 Total Radius of the Topology . . . . . . . . . . . . . . . . . . . . . . . . 58
3.3.2 The Node Density in each Corona (for END-BE) . . . . . . . . 59
3.3.3 The Node Density in each Corona (for END-MLT). . . . . . . 60
3.4 Cluster Formation Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.4.1 Cluster setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.4.2 CH Rotation within the Cluster. . . . . . . . . . . . . . . . . . . . . . . 65
3.5 Data Forwarding Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.6 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
3.6.1 Cluster Coverage Rate. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.6.2 Network Lifetime. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.6.3 Residual Energy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4 Efficient Cluster Radius and Transmission Ranges in WSNs. . . . . . . . . 78
4.1 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
4.2 Balanced Energy Depletion Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.3 Cluster Formation Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
4.3.1 Determining the Number of Coronas in Topology . . . . . . . . 87
4.3.2 Calculating the Cluster Radius . . . . . . . . . . . . . . . . . . . . . . . 87
4.3.3 Cluster Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.3.4 CH-to-CH Transmission Capacity . . . . . . . . . . . . . . . . . . . . 89
4.4 Data Forwarding Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.4.1 Intra-cluster Data Forwarding . . . . . . . . . . . . . . . . . . . . . . . . 92
4.4.2 Inter-cluster Data Forwarding . . . . . . . . . . . . . . . . . . . . . . . . 92
4.5 Cluster Maintenance Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4.5.1 CH Rotations in a Cluster . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4.5.2 Cross-corona Data Transmissions . . . . . . . . . . . . . . . . . . . . 93
4.6 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4.6.1 Network Lifetime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.6.2 Residual Energy of each Sensor Node . . . . . . . . . . . . . . . . . 99
4.6.3 Total Number of CH Rotations. . . . . . . . . . . . . . . . . . . . . . . 101
4.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

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