HCDD: Hierarchical Cluster-based Data Dissemination in Wireless Sensor Networks with Mobile Sink

在無線感測網路中，要有效率地對會移動的資料接收點傳送資料，是一個很難的問題。這是因為受限於感測器的有限資源，如能源、存取空間、還有有限的計算能力。雖然把移動資料接收點的位置資訊廣播到整個網路上是一個直覺的解決方法，但是它會很容易的把感測器的電池能源用完。所以，我們提出一個以階層式叢集導向的方法，叫HCDD，它在很少的負擔下去傳送資料。此外，不像其它的文獻所提，我們的方法能在沒有點的位置資訊就能運作。換句話說，它不需要任何像GPS這類昂貴且花能源的裝置。最後我們會在模擬結果中，展現出HCDD比TTDD等類似的方法，有比較好的資料傳送、較長的網路生命、和比較低的額外負擔Data Dissemination to mobile sinks within wireless sensor networks is a difficult problem due to limited resources of sensors, such as energy, storage capacity, and computing capability. Although flooding the location information of mobile sinks seems to be a naive solution to sink mobility, it drains the sensors of their battery power rapidly. Thus, we propose a hierarchical cluster-based approach, named HCDD, to disseminate data to the mobile sink with light overhead. In addition, unlike other works, our approach operates without location information of nodes, that is, it does not need any expensive and power-consuming GPS devices. Finally, we will show that HCDD has better data delivery, longer network lifetime, and lower overhead compared with TTDD-like methods in simulation results.- Title - 致謝 - Abstract in English - 中文摘要 1 Introduction 1 1.1 Background 1 1.2 An Illustration of Application with Mobile Sink 2 1.3 Motivation 2 1.4 Diferences of Routing Between Sensor Networks and Ad Hoc Networks 3 1.5 Problem Refinement 4 1.6 Our Contribution 4 1.7 Paper Organization 5 2 Related Works 6 2.1 Flooding Approach 6 2.2 Grid-Like Approach 7 2.3 Registration Approach 9 3 A GPS-Free Solution: Hierarchical Cluster-based Data Dissemination(HCDD) 11 3.1 Our Intuitive Idea 11 3.2 System Description 12 3.3 Cluster Formation 14 3.4 Sink Location Registration 15 3.5 Data Delivery 16 4 Performance Evaluation and Discussion 18 4.1 Simulation Environment and Setup 18 4.2 Infuence of Diferent Parameters Used in Cluster-based and Grid-based Methods 21 4.2.1 Overhead 21 4.2.2 Network Lifetime 21 4.2.3 Delivery Rate and Successfully Received Packets 23 4.2.4 Average Packet Route Length 28 4.2.5 Data Delivery Latency 28 4.3 Comparison Between Cluster-based Approach and Grid-based Dissemination Approach 32 4.3.1 Overhead 32 4.3.2 Network Lifetime 33 4.3.3 Delivery Rate and Successfully Received Packets 34 4.3.4 Average Packet Route Length and Data Delivery Latency 36 4.4 Comparisons From Another Viewpoint 37 4.4.1 Overhead and Network Lifetime 37 4.4.2 Successfully Received Packets 39 4.4.3 Relation Between Route Length and Delivery Latency 39 5 Conclusions and Future Works 42 A Max-Min D-Cluster Formation Algorithm 43 A.1 Approach Description 43 A.1.1 Data Structures Used in the Algorithm 43 A.1.2 Term Definition 44 A.1.3 Basic Idea 4