資料收集是無線感測網路(Wireless Sensor Networks, WSNs)中最重要的應用之一。研究表明，使用移動感測器收集數據在無線感測網路的優勢顯著，譬如提高感測器節點的能量效益和延長網絡壽命。 然而，移動感測器的速度有限，從而導致較大的延遲，導致靜態感測器節點存在數據新鮮度或緩衝區溢出等問題。 為了减少移動感測器拜訪靜態感測節點的路徑長度，本研究提出了一種以調變傳輸速率為主的資料收集算法。 本研究不僅保證了每個靜態節點資料傳輸的完整性，而且透過為每個靜態感測器使用合適的傳輸速率，减少了移動感測器移動路徑的長度。最後，透過效能評估，該方法可以顯著縮短移動感測器的路徑長度，並且能够完整有效地採集每個感測器的數據。

Data collection is one of the most basic and important applications in wireless sensor networks. Recent studies have shown that the use of mobile sensors to collect data has brought many benefits to wireless sensor networks, such as improving the energy efficiency of sensor nodes and extending the network lifetime. However, the limited speed of mobile sensors leads to large delay, resulting in data freshness or buffer overflow problems in static sensor nodes. Based on adaptive rate control, a data collection algorithm is proposed to reduce the length of mobile path when mobile sensors collect data from static sensor nodes. The algorithm not only ensures the integrity of data collection of each static node, but also reduces the length of the mobile sensor's moving path by using the appropriate transmission rate for each static sensor. Through a large number of simulations, the experimental results show that our method can significantly shorten the path length of mobile sensors, and can collect the data of each sensor completely and effectively.

List of Figures	IV
List of Tables	V
Chapter 1. Introduction	- 1 -
Chapter 2. Related Works	- 5 -
Chapter 3. Network Environment and Problem Statement	- 9 -
3.1 Network Environment	- 9 -
3.2 Problem Statement	- 11 -
Chapter 4. Data Collection Algorithm	- 14 -
4.1 Construct Initial Path Phase	- 15 -
4.2 Path Reduction Phase	- 18 -
4.3 The Proposed MDCM Algorithm	- 29 -
Chapter 5. Performance Evaluation	- 31 -
Chapter 6. Conclusions	- 42 -
References	- 43 -
 

Fig. 1.  The radius of each ring region corresponds to the distance of each modulation mode.	- 19 -
Fig. 2.   The radius of each ring region corresponds to the distance of each modulation mode.	- 21 -
Fig. 3.  The example of data collection segment  gi of sensor  si.	- 23 -
Fig. 4.  All sensors are partitioned into several group.	- 25 -
Fig. 5.  The construction of segment gi for sensor si.	- 26 -
Fig. 6.  The data collection segment gi of  all sensors si can be constructed.	- 26 -
Fig. 7.  Connect all segments of the sensors.	- 28 -
Fig. 8. The procedure of Mobile Data Collection Algorithm.	- 30 -
Fig. 9.  Compare the path length of three algorithms in a round.	- 33 -
Fig. 10.  Compare the effective index with different data volume of three algorithms.	- 34 -
Fig. 11. Compare the effective index and buffer size of three algorithms by 20 CPs.	- 35 -
Fig. 12. Compare the improvement ratio of ANN&GA.	- 37 -
Fig. 13. Compare the improvement ratio of CORL2.	- 38 -
Fig. 14. Impact of the number of sensors on the network lifetime by applying difference algorithms.	- 39 -
Fig. 15. Impact of the number of sensors on the energy consumption of mobile sensor by applying difference algorithms.	- 40 -
Fig. 16.  Comparison of energy consumptions of three algorithms.	- 41 -


Table I  Machine type communication (MTC)	- 2 -
Table II  Simulation Setting	- 31 -

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