M2M網路是新興的多對多通信技術。M2M網路中的每一個裝置節點負責去探測所在位置之資訊，並透過裝置與裝置之間的傳輸，將所得資訊傳回M2M伺服器，以利未來資料統計與整合之用。在M2M網路中，透過資料聚合技術將可有效的延長整體M2M的壽命。但是在M2M網路中，針對資料聚合的研究，大部分都僅探討聚合點的選擇以及路由演算法，在聚合終止條件上的研究較為稀少。本論文之目的是探討封包緩衝時間以及封包聚合數量所造成的影響。
論文中提出一個分析的模組來探討資料聚合所造成的傳輸延遲以及能量號所。本論文也開發了一個模擬程式來搭配我們的數學分析模組來探討封包緩衝時間以及聚合數量所造成的影響。模擬的數據顯示封包緩衝時間的長短對能源消耗有很大的影響；更發現透過封包聚合數量能夠有效縮減傳輸延遲。本論文提供使用者在M2M網路中，設定封包緩衝時間以及聚合數量的參考，使得整體M2M網路的壽命能夠延長，並能更容易地計算出傳輸延遲以及整體網路中的能源消耗。

Machine-to-Machine (M2M) networks are increasingly proposed for applications focused on many-to-many communication, where a sensor device is responsible for sensing data in its located area. Applying data aggregation is an efficient way to prolong the lifetime of M2M network. However, most previous M2M works only focus on routing algorithms and finding aggregation points. The objective of this thesis is to study the effects of buffering time and maximum buffered packets in data aggregation.
We devise an analytical model to compute the delivery delay and energy efficiency in data aggregation. Then we develop an extensive simulation to accompany with analytical model to investigate the effects of buffering time and maximum buffered packets. Numerical results show that buffering time significantly affects energy consumption. Moreover, we observe that limiting maximum buffered packets in aggregation mechanism can significantly decrease delivery delay. Our study provides guidelines to set the buffering time and maximum buffered packets in data aggregation.

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