臺灣博碩士論文加值系統

由於感測器裝置受限於硬體本身的緣故而使得可利用資源受到限制，在資料繞送與資料收集機制方面有效的電力使用是一個很重要的課題，為了長期的對事件區域來收集其環境資訊，我們在無線感測網路環境中提出了一個以網格為基礎的負載平衡資料收集機制，在每一個網格中會推舉出一個感測器成為此網格的掌控者，而其餘感測器則進入休眠模式，掌控者會負責偵測周遭的環境資訊以及與其他網格的掌控者進行資料交換，一個完整的資料收集過程可以分成兩個部分：資料聚集階段以及資料傳遞階段，在資料聚集階段中，每當掌控者電力下降一個等級，便會決定是否轉移到新的資料聚集點來取代原本電力低落的資料聚集點去負責收集其餘掌控者的資訊，資料傳遞階段則是以地理及電力資訊為基準的繞送方式來進行資料回報，所以在本論文中我們提出了負載平衡機制來分散無線感測網路的中網格掌控者的工作責任來延長整體網路的壽命，而我們的實驗結果跟現有的方式比較也有較好的效能呈現。

Since sensor devices have limited resource constraints, design of energy aware routing or gathering algorithm is great important issue. In order to collect environmental information from event region over a long period of time, we propose a load-balancing scheme named GL scheme based on grid structure for data gathering in wireless sensor networks. In this scheme, each grid selects a sensor node as grid header to sense information and communicate to other grid headers. A complete data gathering process can divide into two phase, data aggregation phase and data dissemination phase. In data aggregation phase, it determinates a new source to replace old low energy source, and it collects information from other grid in event region. In data dissemination phase, it uses a method liked geographic and energy aware routing to route data. Therefore, we adopt GL scheme to distribute grid header’s responsibility. Finally, our simulation results show better performance than existing approaches.

Chapter 1 Introduction.............................1
1.1 Background......................................1
1.2 Motivation......................................2
1.3 Thesis Organization.............................3
Chapter 2 Related Work.............................5
2.1 CODE............................................5
2.2 Range Query.....................................7
2.3 EADA...........................................10
Chapter 3 Load-balancing for Data Aggregation.....14
3.1 Global Positioning System (GPS)................14
3.2 Grid Structure.................................14
3.3 Header Election................................16
3.4 GL Scheme for Data Aggregation.................16
Chapter 4 Load-balancing for Data Dissemination...21
4.1 Distances from Source to Sink..................21
4.2 Next Grid Selection............................22
4.3 GL Scheme for Data Dissemination...............22
Chapter 5 Experimental Results....................24
5.1 Lifetime.......................................25
5.2 Sensor Utility.................................26
5.3 Delay Time.....................................27
Chapter 6 Conclusion..............................29
Chapter 7 Future Work.............................30
References.........................................31

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