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研究生: 洪振洲
Jen-Jou Hung
論文名稱: 在行動計算資料廣播環境中節省能源的資料存取方式之研究
Energy Efficient Data Access Schemes for Data Broadcast in Mobile Computing Environments
指導教授: 呂永和
yungho Leu
口試委員: 葉耀明
Yao-Ming Yeh
連耀南
Yao-Nan Lien
陳秋華
Chyouhwa Chen
王有禮
Yue-Li wang
陳錫明
Shyi-Ming Chen
學位類別: 博士
Doctor
系所名稱: 管理學院 - 資訊管理系
Department of Information Management
論文出版年: 2006
畢業學年度: 94
語文別: 英文
論文頁數: 98
中文關鍵詞: 行動計算索引快取重新取得資料廣播
外文關鍵詞: data broadcast, mobile computing, index caching, re-access
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  • 由於行動裝置的能源十分有限,許多學者都致力於尋找在行動運算環境之中
    降低的行動裝置能源使用量的方法。其中一種相當有效的方式,就是在廣播頻道中播放資料項目的索引。因此,在目前相關廣播環境的研究之中,有許多的結果都是有關於如何建立更有效的索引。為了能夠更進一步的降低能源的使用量,在本論文之中,我們提出了兩種嶄新的作法。在第一種作法之中,我們將快取在廣播頻道中播出的索引。並且我們也將談到如何使用已經被快取在客戶端的索引資料項目。此外,我們也提出了兩種索引快取空間的管理策略。 分別叫做:
    lower-level-index-first, 簡稱為LLIF, 與 cut-plane-first,簡稱為CPF,兩種方式。 LLIF將優先快取索引樹底層的節點,而CPF則傾向於將索引樹的一組切面(cut-plane)保留在快取之中。 我們執行了廣泛的實驗,並將實驗結果與LRU
    和LRFU兩種知名的快取管理方式比較。實驗的結果證明,索引快取將能有效的降低調校時間(Tuning time) 而並不會使反應時間(Access Time)增加。並且,針對調校時間而言,當客戶端對資料的喜好不集中時,CPF 的效果最好。而當客戶端的快取空間很小, 並且對資料的喜好十分集中時, LLIF將有最低的調校時間。 而針對反應時間而言, LLIF 的等待時間一直是最短的。

    在論文中提出第二種方式之中,我們考慮客戶端使用資料快取來降低調校時間與反應時間的情況。為了要使快取資料項目可以用來回答客戶端的查詢,客戶端必須維護資料內容與伺服器端資料內容的一致性。當伺服器端資料內容改變時,客戶端必須由伺服器端取回新版本的資料內容後,才能用來回答查詢。這種由伺服器端取回新版本的資料內容的動作,在這篇論文中,我們定義為re-access。Re-access一個被異動過的快取資料項目是十分浪費時間與能源的。在這篇論文之中,我們利用過期資料項目中紀錄的bucket_id 來加速重新取得資料的過程。 我們稱這一個新的方式為 re-access scheme。 除了描述re-access scheme的詳細內容外,我們也透過模擬實驗與數學分析的方式來求算re-access scheme 的效率。 實驗的結果證明,re-access scheme確實能有效的降低重新取得一個快取資料項目時所需的調校時間。並且根據實驗結果,我們發現,當資料客戶端查詢頻率的很高或伺服器端異動資料頻率很低時,re-access scheme 將非常的有效率。 並且,re-access scheme 最大的特點是,當廣播結構發生改變時,re-access scheme 仍然可以使用。


    Due to the limited power supply of mobile devices, much research has been done on reducing the power consumption in mobile computing environments. Since supporting indices on the broadcast data items can effectively reduce the power consumption of the mobile clients, most of the existing research on data broadcasting has focused on designing efficient indexing schemes. To further reduce the energy consumption, we propose in this thesis two novel approaches. In the first approach, we propose to cache indices on the mobile clients and use them to access the broadcast data items. To manage the cached indices, we propose two new cache management policies. The lower-level-index-first policy caches the index nodes that are at the lower level of the index tree, while the cut-plane-first policy caches the index nodes that belong to a cut-plane of the index tree. Through experiments, we compare the performance of the
    two proposed policies with some existing policies in terms of tuning time and access time. The experiments show that index caching significantly reduces the tuning time of a mobile client without increasing its access time. In terms of tuning time, the experiments show that, when the access pattern of a mobile client is not skew, the cut-plane-first policy outperforms the lower-level-index first policy, LRU and LRFU. When the mobile client has limited cache and high skew of data access, the lower-levelindex- first policy outperforms the cut-plane-first policy, LRU and LRFU. In terms of access time, the lower-level-index first policy always outperforms the cut-plane-first
    policy, LRU and LRFU.

    In second approach, we explore the efficient data re-access problem in data broadcast of a mobile computing environment with data caching. Data caching is used in data broadcast with the aim of reducing both access time and tuning time. For the cache data items of a mobile client to be useful, they need to remain consistent with the source data items in the server. When the data items are updated in the server, a mobile client needs to access the new content of its cached data items from the server.
    The operation to access the new content of a cached data item is called a re-access operation in this thesis. The re-access operation is time- and energy-consuming since a mobile client needs to tune in to the broadcast channel for the data item. In this thesis, we propose to uses the bucket id of a cached data item to speed up the reaccess operations. We call this approach the re-access scheme. We analyze the performance of the re-access scheme and validate the analysis results through experiments. The experiments show that the re-access scheme improves the performance of data caching by significantly reducing the tuning time in re-accessing a data item. The experiments
    also show that the proposed re-access scheme is especially effective when the query frequency on the mobile client is high or when the data update frequency on the server is low. Besides, the proposed re-access scheme is robustness in the sense that it allows the broadcast server to update its broadcast structure in data broadcasting.

    Chinese Abstract v Abstract vi Acknowledgement viii Table of Contents ix List of Figures x List of Tables xiii 1 Introduction 1 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Data broadcast approach . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.3.1 Index caching Scheme . . . . . . . . . . . . . . . . . . . . . . 5 1.3.2 Data re-access Scheme . . . . . . . . . . . . . . . . . . . . . . 6 1.4 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.5 Overview of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . 8 2 Related Works 9 2.1 Data Broadcast Approach . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2 Data Caching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3 Efficient Index Caching for Data Dissemination in Mobile Computing Environments 13 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.2 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.2.1 The Broadcast Structure . . . . . . . . . . . . . . . . . . . . . 15 3.2.2 Index Organization . . . . . . . . . . . . . . . . . . . . . . . . 15 3.3 Index Caching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.3.1 Using a Cached Index . . . . . . . . . . . . . . . . . . . . . . 18 3.3.2 Tuning Reduction and the Location of an Index Node . . . . . 20 3.4 Cachemanagement . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.4.1 CacheManagement Policies . . . . . . . . . . . . . . . . . . . 22 3.4.2 The Lower-Level-Index-First Management Policy . . . . . . . 22 3.4.3 The Cut-Plane-First Management Policy . . . . . . . . . . . . 24 3.5 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.5.1 Experiment 1: Effect of Cache Size on Tuning Time . . . . . . 32 3.5.2 Experiment 2: Effect of Cache Size on Access Time . . . . . . 34 3.5.3 Experiment 3: Effect of Data Access Skew on Tuning Time . . 35 3.5.4 Experiment 4: Effect of Data Access Skew on Access Time . . 36 3.5.5 Summary of the Effects of Cache Size and Data Access Skew . 37 3.5.6 Experiment 5: Effect of Height of Index Tree . . . . . . . . . 38 3.5.7 Experiment 6: Effect of Degree of Index Tree . . . . . . . . . 40 4 An energy efficient re-access scheme for data caching in data broadcast of a mobile computing environment 42 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.2 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.2.1 Index Tree Construction of EPR. . . . . . . . . . . . . . . . . 44 4.2.2 Generation of Broadcast Structure . . . . . . . . . . . . . . . 45 4.2.3 AModified Broadcast Structure . . . . . . . . . . . . . . . . . 47 4.3 Re-access with Fixed Broadcast Structure . . . . . . . . . . . . . . . 48 4.4 Re-access with Dynamic Broadcast Structure . . . . . . . . . . . . . . 50 4.4.1 Patch report . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4.4.2 Using a patch report . . . . . . . . . . . . . . . . . . . . . . . 53 4.4.3 Query Execution . . . . . . . . . . . . . . . . . . . . . . . . . 57 4.5 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 4.5.1 Performance of Re-access Scheme . . . . . . . . . . . . . . . . 61 4.6 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 4.6.1 Effect of Query Frequency . . . . . . . . . . . . . . . . . . . . 68 4.6.2 Effect of the Cache Size . . . . . . . . . . . . . . . . . . . . . 70 4.6.3 Effect of the Data Update Frequency . . . . . . . . . . . . . . 73 4.6.4 Effect of the Broadcast Structure Update Frequency . . . . . 74 5 Conclusions 76 Bibliography 79

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