一個輕量以移動習慣優先為基礎的動態位置管理機制 - 使用道路資訊與全球定位系統

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鍾享材(Hsiang-Tsai Chung) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

一個輕量以移動習慣優先為基礎的動態位置管理機制 - 使用道路資訊與全球定位系統
(A Light-Weight Moving Preferences BasedDynamic Location Management Scheme Using Road Map and GPS)

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摘要(中)

中文摘要
在未來的微細胞個人通訊服務系統(Personal Communication Service, PCS)中預期將會是高使用者密度與高移動性的世界。而在未來的個人通訊系統中，行動位置管理將無可避免的產生大量的訊息傳遞。過去有不少基於不同策略而衍生出的動態行動位置管理機制被提出，試圖找到最佳化的門檻值，來降低包含位置更新( location update )以及呼叫(paging)等兩者為主的系統資源消耗。以速度為基礎的方法，是以距離為基礎方法的延伸，被認為是傳統動態管理機制最好的方法。然而這些過去的動態位置管理機制，由於缺乏有效的使用者移動預測(mobility prediction)的能力，只考慮對位置區域(Location Area)的大小作最佳化，而忽略位置區域的形狀長相。使得這些機制在使得當使用者在比較快速移動的情況下，將無法很有效的降低位置管理機制對系統資源的消耗。
為了滿足先前所提到使用者對高移動性的基本要求，在這篇論文中我們提出一個叫做 “移動習慣優先 (Moving Preferences Based, MPB)” 的輕量級的行動位置管理機制來做使用者移動預測。另一方面，由於高移動性的特質只有在使用者在搭乘交通工具的情況才得以展現，因此在我們提的方法中採用了地圖道路資訊以及全球定位系統。而使用者移動習慣的資訊可以從長時間使用者移動紀錄中得到，而我們所提方法的概念和其他人不同的地方在於，我們對使用者移動的目的地感興趣，而其他人則是對使用者所經過基地台或是道路的順序感興趣。由於我們的方法不需要完整紀錄包含所有節點與邊線的使用者移動歷史資料，因此具有輕量便利的特色，並且提供更好的彈性與擴充性。再者我們的方法不僅止於短距離預測有效用，甚至對於更長一點的距離也能做有效的預測。而依據上面所述的特色與概念，我們提出了一個新的成本模型同時考量最佳化的位置區域的大小與形狀，來找尋最佳位置更新的門檻值降低行動管理機制對系統資源的消耗。而實驗數據的結果顯示出我們所提的方法和過去傳統的方法相比較，在對系統資源消耗上的確有個很相當程度的改善。

摘要(英)

ABSTRACT
Future microcellular Personal Communication Service (PCS) networks are expected to be high user density and high mobility. Location managements in the PCS networks will incur a large amount of signaling traffic. Several dynamic location management schemes based on different strategies are proposed to reduce the signal costs both of location update (LU) and paging (PG). The velocity-based scheme, an extension of distance-based, is known as the best of conventional dynamic location update schemes. However, due to lack of effective mobility prediction capabilities, these schemes which consider only the optimal size of the LA regardless the optimal shape of the LA will perform inefficiently when mobile terminals move in a higher speed.
To satisfy user requirements of high mobility mentioned above, we proposed a light-weight dynamic location management scheme called “Moving Preference” for mobility prediction in this paper. On the other hand, since MTs carried in vehicle are the ones demonstrate high mobility, an idea of incorporation of location-based information (i.e. road map & GPS) is introduced in the proposed scheme. The “Moving Preference” which is a mobility prediction technique derived from mobile terminal’s long-term moving history. In our basic idea, we are more interested in the destinations (moving preferences) a mobile terminal is likely to leave or stay rather than the sequence of cells or road segments a mobile terminal is likely to pass in transit. Our scheme features light-weight which does not need to keep track all possible nodes and edges in the moving history of a pecified MT. Thus, provides better flexibility and scalability. Moreover, the mobility prediction of the proposed scheme is effective not only within a short distance, but also a longer one. Based on these features, we introduced a new cost model, both the size and shape of a LA are taken into considerations, to find out an optimal location update threshold for signal costs minimizing. The simulation results indicate that our moving preferences based (MPB) scheme do have a great improvement over conventional ones.

關鍵字(中)

★ 全球定位系統
★ 行動預測
★ 位置管理
★ 位置區域
★ 呼叫
★ 位置更新

關鍵字(英)

★ location management
★ location tracking
★ location area
★ paging
★ location update
★ GPS
★ mobility prediction

論文目次

CONTENTS
Chapter 1. Introduction 1
1.1. The PCS networks 1
1.2. Location Management Evolutions 4
1.2.1. Static Schemes v.s. Dynamic Schemes 6
1.2.2. Mobility Prediction Techniques 7
1.2.3. Positioning Technology (GPS) 9
1.3. Research Issues & Motivation 10
1.4. Goal of Proposed Scheme 11
1.5. Organization of the Dissertation 13
Chapter 2. Related Survey 14
2.1. Dynamic Location Update Schemes Survey 14
2.1.1. Time-Based 15
2.1.2. Movement-Based 15
2.1.3. Distance-Based 16
2.1.4. Velocity-Based 16
2.2. Mobility Prediction Techniques Survey 18
2.2.1. Profile-Based 18
2.2.2. Behavior-Based 19
2.2.3. Road-Topology-Based 21
2.3. Positioning Technology (GPS) 23
Chapter 3. The Moving Preference Scheme 25
3.1. The System Requirements 25
3.2. The Moving Preference 27
3.2.1. Moving Preferences Discovery 29
3.2.2. Moving Preferences Maintenance 30
3.3. Moving Preference Prediction 31
3.3.1. Regular Time Behavior 31
3.3.1. Irregular Time Behavior 32
3.3.1. Totally Unpredictable Behavior 33
3.3.1. The Prediction Diagram 35
3.4. Route to Destination Selection 37
3.4.1. Route to Destination Selection on Initial Stage 37
3.4.2. Route to Destination Selection on the halfway 38
3.5. The Optimal Cost Model and Numerical Analysis 39
Chapter 4. Simulation Results 43
4.1. Simulation Environment and Related Parameters 43
4.2. Regular Moving Preference Simulation 46
4.3. Irregular Moving Preference Simulation 59
Chapter 5. Conclusion and Future Work 63
Reference 65

參考文獻

Reference
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指導教授

吳曉光(Eric Hsiaokuang Wu)

審核日期

2004-9-30

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