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姓名	胡為凱(Wei-Kai Hu)  查詢紙本館藏	畢業系所	資訊工程學系
論文名稱	在無線感測網路中之定位與時間同步演算法 (Localization and Time Synchronization for Wireless Sensor Networks)
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摘要(中)	由於近代科學及技術的大幅度進步，致使微小且低成本之感測器之得以實現，由這些微型感測器所組成之無線感測器網路正逐漸受到注目，目前也已利用在各種應用領域，如動物棲息環境之監測、健康照護、大樓與家庭自動化和交通流量控制等。在各式各樣的線感測器網路應用中，由感測器所偵測到的數據通常需要結合偵測當下的正確時間與位置資訊，才得以讓使用者用進一步的分析和處理。此外，許多感測器網路之協定任務及演算法要求每個感測器維持一個全域計時器，以及得知自身目前的所在位置，以便這些任務或演算法可以正確執行。因此，時間同步與定位是無線感測器網路中必要且重要的兩項服務。在傳統的無線網路中，已設計出許多方法來達成時間同步與定位，但無線感測器網路因其獨有之特性，如有限的電量供給和大規模之網路環境等，使得其與傳統無線網路有所不同，為使無線感測器網路具備此兩項服務，則必須發展新的解決方法。 為使所有感測節點維護一個同步於參考節點的計時器，我們提出一個在無線感測器網路中多步跳躍的時間同步協定，在此協定中，未同步節點藉由估算出與參考點間的時脈飄移率與時間偏移量，使自身達成同步狀態，而且利用週期性的重新同步程序，一些未能達成時間同步的情況，如節點損壞或網路拓樸改變等，皆可輕易地克服。我們並在Berkeley大學開發的MICAz硬體平台中實作我們的時間同步協定，而實驗所採用網路設定分別為5個感測器及18個感測器的多步跳躍拓樸環境，另外重新同步週期長度則各設定為30秒及300秒。實驗結果顯示，執行我們所設計的同步協定的節點，其平均同步誤差約略在數個毫秒左右，亦比之前他人所提出的同步協定表現較好。我們所提出的同步協定只利用較少的通訊花費(communication overhead)，卻能建構出強健的同步環境給予網路中之節點，當不同的應用情境要求不同的同步準確性時，我們的同步協定可藉由調整同步週期來達成其需求。 另一方面，為了在行動感測網路中取得節點的位置資訊，我們亦提出了一個自我定位方法，此方法改善了先前基於序列蒙地卡羅法的定位方法。我們提出的定位方法作用於網路中有部分節點(錨節點)已事先得知其自身的位置，未知位置的節點將會利用一群合法的位置樣本來代表目前自身的位置，而此合法的位置樣本，主要由來自兩步跳躍內的已知位置鄰居節點的位置資訊，以及一步跳躍內未知位置但已初步定位的鄰居節點的位置資訊，來過濾取得。此外，我們也提出了移動方向預測方法，來進一步地加強定位的精確度。我們亦透過各種的節點移動模型，和不同的節點移動速率的網路情境設置，來進行模擬實驗，其結果顯示我們所提出的定位方法，在大部分的網路情境中，其表現較其它基於序列蒙地卡羅法的定位方法好。由於利用了未知自身實際位置的鄰居，所提供的初步估算的位置資訊，以致我們的定位方法可以在低錨節點(Anchor)密度的網路環境中持續運作。再者，在我們的定位方法中，依據每個節點在每個時段所估算出的取樣區域面積，來決定其位置樣本之個數，如此便降低了運算成本與佔用的記憶體空間。而為了降低網路傳輸成本，我們設計了一個簡易扇形化方法，此方法主要將未知節點的可能所在區域以數個扇形來表示。我們亦提出了一個新的移動方向限制條件，來取得更準確的位置樣本來估算所在位置。
摘要(英)	Wireless sensor networks (WSNs), which are formed by tiny and low-cost sensor nodes derived from the recent advances of science and technology, have been gradually paid more attention and now are being used for a variety of application areas, including environmental and habitat monitoring, health care, building/home automation, traffic control, etc. Among various WSN applications, the sensor readings from network nodes will be valuable to users for advance analyzing or processing if the correct time and location information at the moment is attached to them. Moreover, many collaborative tasks or algorithms need each sensor node to maintain a global clock and be aware of its current locations at the same time so that the tasks or algorithms can be run well. Thus, both time synchronization and localization for sensor nodes are essential and important services in WSNs. There have been many schemes proposed to realize these two services in traditional wireless networks. However, wireless sensor networks are rather different from traditional wireless networks due to restricted energy resource, large network scale and so on. Hence, new solutions for these two services must be proposed specially in WSNs. To let all nodes maintain a global clock which is synchronized to that of a reference node, we design a time synchronization protocol for multi-hop WSNs. In the proposed protocol, unsynchronized node estimates the clock drift ratio and offset with the reference node to become synchronized. By periodical re-synchronization, the un-synchronization conditions such as nodes failures or topology change can be easily overcome. We implement our protocol in the Berkeley MICAz platform. The experimenting scenarios are 5-node and 18-node multi-hop topologies, and the re-synchronization periods are 30-second and 300-second. The experiment results show that the average synchronization errors of all nodes run with our protocol are ranged within several micro-seconds and are less than those of the previous protocol. Our proposed protocol uses lower communication overhead and establishes more robust synchronization situations for all nodes in the network. The synchronization accuracy required by different applications can be achieved by using different re-synchronization periods. To obtain the node location information for mobile sensor networks, we also propose a localization scheme to improve the localization accuracy of previous work based on SMC (Sequential Monte Carlo). It operates under the assumption that a few part of sensor nodes know their positions. The valid samples to represent sensor nodes’ possible locations are filtered upon the location information from the location-aware nodes (anchor nodes) within two hops as well as that from the location-unaware nodes within one hop of which the locations have been initially estimated. In addition, we propose a moving direction predicting method to further enhance the accuracy of the location estimates. Simulation results show that our proposed localization algorithm performs better than other SMC-based algorithms in most network configurations with various mobility models and different moving speeds. Since the estimated location information of neighboring nodes unknown to their actual positions is utilized, our localization scheme can still work well for low anchor-density networks. Furthermore, each node’s number of samples in our proposed scheme is adapted according to the estimated sampling region at each time slot. Thus, the computation cost and memory occupation can be obviously decreased. To minimize the network traffic cost, we use a simple sectoring scheme to represent the possible located region of each location-unaware node. We also propose a novel moving direction constraint to refine more accurate samples for location estimate.
關鍵字(中)	★ 定位 ★ 無線感測器網路 ★ 時間同步 ★ 時脈漂移 ★ 非測距	關鍵字(英)	★ range-free ★ localization ★ time synchronization ★ Wireless Sensor Networks (WSNs) ★ clock drift
論文目次	Table of Contents vi List of Figures viii List of Tables x Chpater 1 Introduction 1 1.1 Wireless Sensor Networks 1 1.2 Motivation 4 1.3 Contributions 8 1.4 Organization of this Dissertation 10 Chpater 2 Related Works 12 2.1 Time Synchronization Schemes in WSNs 12 2.2 Localization Schemes in WSNs 18 2.2.1 Localization Approaches for Static WSNs 18 2.2.1.1 Range-based Localization 18 2.2.2.1 Range-free Localization 22 2.2.2 Localization Approaches for Mobile WSNs 30 Chpater 3 Ratio-based Time Synchronization Protocol 36 3.1 Our Proposed Protocol 36 3.1.1 The Synchronization Procedure 36 3.1.2 Achieving Multi-hop Time Synchronization 40 3.2 Experiments 43 3.2.1 Synchronization Errors with a Single-hop Topology 44 3.2.1 Synchronization Errors with Multi-hop Topologies 45 3.3 Summary 52 Chpater 4 The Proposed Localization Scheme 53 4.1 Our Proposed Scheme 53 4.1.1 Sample selection phase 54 4.1.2 Neighbor constraint exchange phase 57 4.1.3 Refinement phase 60 4.2 Performance Evaluation 63 4.2.1 System Model and Parameters 63 4.2.2 Localization error 66 4.2.3 Number of Samples 67 4.2.4 Impact of the anchor node density 68 4.2.5 Impact of the number of normal nodes 69 4.2.6 Impact of the moving speed 70 4.2.7 Impact of the irregular communication range 71 4.2.8 Impact of the mobility model 73 4.2.9 Communication Cost 75 4.3 Summary 77 Chpater 5 Conclusions and Future Works 78 5.1 Contributions 78 5.2 Future Work 80 Bibliography 82 Publications 90
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指導教授	許健平(Jang-Ping Sheu)	審核日期	2010-6-30
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