發(fā)布時間：2018-08-29 12:57

【摘要】：近年來,在線社交網(wǎng)絡(luò)(Online Social Network,OSN)取得了巨大成功,在全球范圍內(nèi)擁有數(shù)十億用戶。通過OSN,用戶可以結(jié)交新的朋友或與自己的朋友共享信息。目前比較流行的商用OSN包括Facebook,Twitter,人人網(wǎng),新浪微博,騰訊微信等,它們都采用了集中式數(shù)據(jù)存儲架構(gòu),所有的用戶數(shù)據(jù)集中存儲到服務(wù)提供商所運維的服務(wù)器上。服務(wù)提供商可以使用和分析這些數(shù)據(jù),甚至直接將之出售給第三方,破壞了用戶隱私。因此,這種集中式在線社交網(wǎng)絡(luò)(Centralized Online Social Network,COSN)中存在嚴重的用戶數(shù)據(jù)隱私泄露問題,已經(jīng)引起了廣泛的關(guān)注。在此背景下,分布式在線社交網(wǎng)絡(luò)(Decentralized Online Social Network,DOSN)被提出來解決上述用戶數(shù)據(jù)隱私泄露問題。盡管DOSN還不如COSN流行和成熟,但是業(yè)界對它的研究非�；钴S,正處于快速發(fā)展時期。在DOSN中,為了保護隱私,用戶數(shù)據(jù)繞過服務(wù)器直接在朋友圈內(nèi)存儲和轉(zhuǎn)發(fā)。DOSN雖然能防止服務(wù)提供商泄露用戶隱私數(shù)據(jù),但是存在數(shù)據(jù)可用性低下的問題:當(dāng)某一用戶處于離線狀態(tài)時,其它用戶不能訪問存儲在該離線用戶處的數(shù)據(jù)。為了在數(shù)據(jù)隱私保護約束條件下提高數(shù)據(jù)可用性,必須設(shè)計適用于DOSN場景的數(shù)據(jù)存儲方案及相應(yīng)的優(yōu)化策略,這是目前DOSN研究中的最大挑戰(zhàn)之一。DOSN具有如下特點:1)用戶動態(tài)性高;2)接入終端存儲資源有限;3)大部分用戶的朋友圈不大;4)社交數(shù)據(jù)以小數(shù)據(jù)為主,且很少修改。本文通過深入研究已有的DOSN數(shù)據(jù)存儲技術(shù)和存儲優(yōu)化相關(guān)工作發(fā)現(xiàn),已有工作主要關(guān)注用戶動態(tài)性,而忽略了其它特點對數(shù)據(jù)存儲優(yōu)化目標(biāo)的影響。針對現(xiàn)有工作的不足,本文系統(tǒng)地研究了以數(shù)據(jù)隱私保護約束下提高數(shù)據(jù)可用性為主要目標(biāo)的DOSN數(shù)據(jù)存儲和存儲優(yōu)化問題,主要包括如下幾個方面:1.存儲容量敏感的DOSN數(shù)據(jù)可用性建模與分析已有的DOSN數(shù)據(jù)存儲方案通常假設(shè)朋友總是能為用戶提供足夠的存儲容量保存用戶發(fā)布的數(shù)據(jù),然而,這個假設(shè)在DOSN中是不合適的。為了保證不泄露用戶隱私,未受保護的用戶隱私數(shù)據(jù)只能存儲在朋友圈內(nèi)。而如下原因?qū)?dǎo)致朋友圈內(nèi)的總存儲容量有限:1)在線朋友數(shù)量有限;2)DOSN用戶通常使用移動智能設(shè)備,它們的存儲容量通常有限。直觀地,有限的朋友圈總存儲容量降低了數(shù)據(jù)可用性。但是僅僅知道這一粗略結(jié)論是不夠的,我們還希望獲悉存儲容量對數(shù)據(jù)可用性的影響程度,以確定是否有必要進行數(shù)據(jù)存儲優(yōu)化。因此,在重新設(shè)計DOSN數(shù)據(jù)存儲方案之前,有必要定量分析朋友圈可貢獻的總存儲容量與所能達到的數(shù)據(jù)可用性之間的關(guān)系,這是本文要解決的首要問題。針對此問題,本文提出了一個存儲容量敏感的數(shù)據(jù)可用性模型,深入分析了朋友圈可貢獻的總存儲容量與所能達到的數(shù)據(jù)可用性之間的定量關(guān)系。此外,朋友圈內(nèi)的在線朋友高度動態(tài)變化,影響了朋友圈可貢獻的總存儲容量,進而導(dǎo)致數(shù)據(jù)可用性也高度動態(tài)變化。針對這一問題,本文通過預(yù)測朋友圈實時總存儲容量預(yù)測實時數(shù)據(jù)可用性,進一步研究了朋友圈總存儲容量與所能達到數(shù)據(jù)可用性之間的動態(tài)變化關(guān)系。最后,本文還進行了大量實驗,驗證了存儲容量敏感的數(shù)據(jù)可用性模型的有效性�；诖鎯θ萘棵舾械臄�(shù)據(jù)可用性模型,給定預(yù)期數(shù)據(jù)可用性可以確定朋友圈所需的最小總存儲容量,進而可以確定每個朋友所需貢獻的平均最小存儲容量,為應(yīng)用程序存儲容量的分配提供依據(jù);反之,給定朋友圈總存儲容量,可以確定朋友圈所能達到的最大數(shù)據(jù)可用性,從而可以確定預(yù)期數(shù)據(jù)可用性是否能夠得到滿足,并指導(dǎo)下一步的數(shù)據(jù)存儲方案設(shè)計。2.云輔助的dosn數(shù)據(jù)存儲方案cadros如上文所述,dosn中,為了保證用戶隱私不被泄露,數(shù)據(jù)在未受保護的情況下只能冗余存儲在朋友圈內(nèi)。但是dosn是一個高度動態(tài)的網(wǎng)絡(luò),用戶可以隨時添加和刪除朋友,且朋友可以隨時上線和下線,所以朋友圈內(nèi)在線朋友集合和所貢獻的總存儲容量是有限且動態(tài)變化的。如果僅依賴朋友圈冗余存儲用戶數(shù)據(jù),將不能獲得較高的數(shù)據(jù)可用性。以數(shù)據(jù)隱私保護約束下提高數(shù)據(jù)可用性為主要目標(biāo),設(shè)計適用于dosn的數(shù)據(jù)存儲方案是本文要解決的第二個關(guān)鍵問題。針對該問題,本文基于存儲容量敏感的數(shù)據(jù)可用性模型,提出了一種云輔助的dosn數(shù)據(jù)存儲方案cadros,引入云服務(wù)器提高數(shù)據(jù)可用性。當(dāng)朋友圈不能滿足數(shù)據(jù)存儲需求時,將多余數(shù)據(jù)用糾刪碼技術(shù)分片編碼后存儲到云服務(wù)器中,且保證云服務(wù)器中存儲的數(shù)據(jù)片段數(shù)量不超過恢復(fù)原始數(shù)據(jù)所需要的數(shù)據(jù)片段數(shù)量,以防止云服務(wù)提供商獲得原始數(shù)據(jù),從而保護了用戶數(shù)據(jù)隱私。本文定量研究了cadros的數(shù)據(jù)存儲能力,討論了cadros的數(shù)據(jù)可用性,從理論上證明了cadros方案的可行性和有效性;同時還建立了朋友圈內(nèi)朋友動態(tài)行為的概率模型,通過預(yù)測朋友圈將來的數(shù)據(jù)存儲能力和存儲需求,建立了cadros實時數(shù)據(jù)可用性預(yù)測模型,可以為下一步設(shè)計數(shù)據(jù)存儲策略提供依據(jù)。3.社交數(shù)據(jù)在dosn中的存儲優(yōu)化技術(shù)上一研究中的實時數(shù)據(jù)可用性預(yù)測結(jié)果只是表明cadros在給定朋友圈總存儲容量的前提下有能力達到相應(yīng)的數(shù)據(jù)可用性。朋友圈最終是否能獲得預(yù)期的數(shù)據(jù)可用性還依賴于數(shù)據(jù)存儲策略。即使朋友圈能提供足夠的存儲容量,如果沒有一個好的數(shù)據(jù)存儲策略,也不能獲得理想的數(shù)據(jù)可用性。在cadros數(shù)據(jù)存儲方案中,如何基于實時數(shù)據(jù)可用性預(yù)測結(jié)果,針對dosn用戶行為特征,設(shè)計一個適用的數(shù)據(jù)存儲策略是本文要解決的第三個關(guān)鍵問題。針對這一問題,本文進一步優(yōu)化Cadros數(shù)據(jù)存儲方案,研究社交數(shù)據(jù)在DOSN中的存儲優(yōu)化技術(shù),首先提出了一個開銷敏感的數(shù)據(jù)劃分方法和存儲策略,分別確定存儲到朋友圈內(nèi)和云服務(wù)器中的數(shù)據(jù),可充分利用朋友圈可用存儲容量,使系統(tǒng)開銷最小;然后,提出一個可用性驅(qū)動的DOSN數(shù)據(jù)副本放置方法,合理地將數(shù)據(jù)放置到朋友圈內(nèi),可實現(xiàn)預(yù)期的數(shù)據(jù)可用性,且能均衡系統(tǒng)負載,降低系統(tǒng)為實現(xiàn)數(shù)據(jù)可用性所造成的維護開銷。4.社交數(shù)據(jù)在云服務(wù)器中的存儲優(yōu)化技術(shù)如上文所述,Cadros數(shù)據(jù)存儲方案不僅將用戶數(shù)據(jù)冗余存儲在朋友圈內(nèi),還在朋友圈不能滿足數(shù)據(jù)存儲需求時將一部分數(shù)據(jù)存儲到云服務(wù)器中。云服務(wù)器具有長期高可用的特點,因此云服務(wù)器上數(shù)據(jù)的可用性可近似認為達到100%,不存在數(shù)據(jù)可用性問題。然而當(dāng)用戶訪問云服務(wù)器上社交數(shù)據(jù)時,卻存在訪問性能不高的問題。社交數(shù)據(jù)以小數(shù)據(jù)為主,并很少修改。云服務(wù)器通常采用傳統(tǒng)的分布式文件系統(tǒng)來存儲和管理用戶數(shù)據(jù),在處理海量社交小數(shù)據(jù)時性能較低。如何提高云服務(wù)器中社交小數(shù)據(jù)的訪問性能是本文要解決的第四個關(guān)鍵問題。為了解決這個問題,本文首先研究了分布式文件系統(tǒng)處理海量社交小數(shù)據(jù)的性能瓶頸;然后提出了一種輕量級的文件系統(tǒng)iFlatLFS對社交小數(shù)據(jù)進行優(yōu)化存儲和管理。iFlatLFS大大簡化了元數(shù)據(jù)結(jié)構(gòu)和數(shù)據(jù)訪問流程。新的元數(shù)據(jù)總量僅占原元數(shù)據(jù)總量的一小部分,可以被全部緩存到服務(wù)器內(nèi)存中,消除了小數(shù)據(jù)尋址開銷,提高了性能。最后本文在CentOS 5.5操作系統(tǒng)中實現(xiàn)了一個iFlat LFS原型,并集成到了開源分布式文件系統(tǒng)TFS中。本章最后進行了大量實驗,結(jié)果證明,iFlatLFS能夠優(yōu)化存儲海量社交小數(shù)據(jù),大幅提高數(shù)據(jù)訪問性能。綜上所述,針對DOSN數(shù)據(jù)存儲及存儲優(yōu)化問題研究面臨的挑戰(zhàn)和現(xiàn)有工作的分析與總結(jié),本文首先定量分析了朋友圈貢獻的總存儲容量與所能達到的數(shù)據(jù)可用性之間的關(guān)系;在此基礎(chǔ)之上,針對朋友圈總存儲容量有限所導(dǎo)致的數(shù)據(jù)可用性低下問題,提出了一種云輔助的DOSN數(shù)據(jù)存儲方案Cadros,解決了數(shù)據(jù)隱私保護問題,提高了數(shù)據(jù)可用性,并從理論上證明了Cadros方案的可行性和有效性,建立了實時數(shù)據(jù)可用性預(yù)測模型;然后研究了社交數(shù)據(jù)在朋友圈內(nèi)的存儲優(yōu)化問題,基于預(yù)測結(jié)果提出了一種開銷敏感的數(shù)據(jù)劃分方法和存儲策略以及可用性驅(qū)動的數(shù)據(jù)放置方法,可達到預(yù)期的數(shù)據(jù)可用性,且能均衡系統(tǒng)負載,降低數(shù)據(jù)可用性維護開銷;最后研究了社交數(shù)據(jù)在云服務(wù)器中的存儲優(yōu)化問題,設(shè)計了一種高效的輕量級文件系統(tǒng)iFlatLFS,可改善云服務(wù)器上社交數(shù)據(jù)的訪問性能。
[Abstract]:In recent years, the online social network (OSN) has achieved great success, with billions of users worldwide. Through OSN, users can make new friends or share information with their own friends. With centralized data storage architecture, all user data is centrally stored on servers operated and maintained by service providers. Service providers can use and analyze this data, and even sell it directly to third parties, thus destroying user privacy. In this context, distributed online social network (DOSN) has been proposed to solve the problem of user data privacy leakage. Although DOSN is not as popular and mature as COSN, the research on it is very active. In DOSN, to protect privacy, user data is stored and forwarded directly in a friend's circle bypassing the server. Although DOSN can prevent service providers from leaking user's privacy data, there is a problem of low data availability: when a user is offline, other users cannot access the data stored in the offline circle. In order to improve data availability under data privacy protection constraints, data storage schemes and corresponding optimization strategies must be designed for DOSN scenarios, which is one of the biggest challenges in DOSN research. 4) Social data is mainly small data, and rarely modified. Through the in-depth study of existing DOSN data storage technology and storage optimization related work found that the existing work mainly focused on user dynamics, while ignoring other characteristics of the impact of data storage optimization goals. This paper systematically studies the DOSN data storage and storage optimization problem with the main objective of improving data availability under data privacy protection constraints. It mainly includes the following aspects: 1. Storage capacity-sensitive DOSN data availability modeling and analysis. Existing DOSN data storage schemes usually assume that friends always provide sufficient storage for users. Storage capacity holds data published by users, however, this assumption is inappropriate in DOSN. In order not to disclose user privacy, unprotected user privacy data can only be stored in the circle of friends. Energy devices usually have limited storage capacity. Intuitively, limited total Friends storage capacity reduces data availability. But it's not enough to know this rough conclusion. We also want to know how much storage capacity affects data availability to determine whether data storage optimization is necessary. Before the DOSN data storage scheme, it is necessary to quantitatively analyze the relationship between the total storage capacity contributed by the friend circle and the data availability that can be achieved, which is the primary problem to be solved in this paper. In addition, the dynamic changes of the online friends'height in the circle of friends affect the total storage capacity that the circle of friends can contribute to, and consequently lead to a high degree of dynamic changes in data availability. To solve this problem, this paper predicts the real-time data availability by predicting the total real-time storage capacity of the circle of friends. Finally, a large number of experiments are carried out to verify the validity of the storage capacity-sensitive data availability model. Based on the storage capacity-sensitive data availability model, given the expected data availability can be determined. The minimum total storage capacity required by the circle of friends can then determine the average minimum storage capacity that each friend needs to contribute and provide a basis for the allocation of application storage capacity; conversely, given the total storage capacity of the circle of friends, the maximum data availability that the circle of friends can achieve can be determined, thus determining the expected data availability is 2. Cloud-assisted dosn data storage scheme cadros, as mentioned above, in dosn, data can only be stored redundantly in the friends'circle without protection in order to ensure the privacy of users is not leaked. But dosn is a highly dynamic network, users can at any time. Adding and deleting friends, and friends can be online and offline at any time, so the collection of online friends and the total storage capacity contributed by friends are limited and dynamic changes. To achieve this goal, designing a data storage scheme suitable for dosn is the second key problem to be solved in this paper. To solve this problem, a cloud-assisted dosn data storage scheme, cadros, is proposed based on the storage capacity-sensitive data availability model. Cloud servers are introduced to improve data availability. When the Friendship Circle can not meet the data storage needs. In order to prevent cloud service providers from obtaining original data and protect user data privacy, this paper quantitatively studies cadros The data storage capability is discussed, and the data availability of cadros is discussed, which proves the feasibility and validity of the cadros scheme theoretically. At the same time, the probabilistic model of the dynamic behavior of friends in the circle of friends is established. By predicting the future data storage capacity and storage requirements of the circle of friends, a real-time data availability prediction model of cadros is established. The next step is to design the data storage strategy to provide the basis. 3. The real-time data availability prediction results of the research on the storage optimization technology of social data in dosn only show that cadros has the ability to achieve the corresponding data availability under the premise of the total storage capacity of a given circle of friends. It also depends on the data storage strategy. Even if the friend circle can provide enough storage capacity, the ideal data availability can not be achieved without a good data storage strategy. In the cadros data storage scheme, how to design a suitable data storage based on the prediction results of real-time data availability for dosn user behavior characteristics To solve this problem, this paper further optimizes the Cadros data storage scheme and studies the storage optimization technology of social data in DOSN. Firstly, an overhead-sensitive data partitioning method and storage strategy are proposed to determine the data stored in friends and cloud servers, respectively. Make full use of the available storage capacity of the friend circle to minimize the system overhead; then, propose a usability-driven DOSN data replica placement method, reasonably put the data into the friend circle, can achieve the expected data availability, and can balance the system load, reduce the system maintenance overhead to achieve data availability. 4. Social number According to the storage optimization technology in cloud server as mentioned above, Cadros data storage scheme not only stores user data redundancy in the friend circle, but also stores some data in the cloud server when the friend circle can not meet the data storage requirements. The cloud server has the characteristics of long-term high availability, so the data on the cloud server is available. Usability is approximated to 100%. There is no data availability problem. However, when users access social data on cloud servers, there is a problem of poor access performance. Social data is mainly small data and rarely modified. How to improve the access performance of small social data in cloud servers is the fourth key problem to be solved in this paper. To solve this problem, this paper first studies the performance bottleneck of distributed file systems for handling large amounts of small social data, and then proposes a lightweight file system iFlatLFS pair. IFlatLFS greatly simplifies the metadata structure and data access process. The total amount of new metadata accounts for only a small part of the total amount of original metadata and can be cached into the server memory, eliminating the small data addressing overhead and improving performance. Finally, this paper implements it in the CentOS 5.5 operating system. A prototype of iFlat LFS is implemented and integrated into the open source distributed file system TFS. At the end of this chapter, a large number of experiments are carried out. The results show that iFlat LFS can optimize the storage of large amounts of social small data and greatly improve the data access performance. In this paper, firstly, we quantitatively analyze the relationship between the total storage capacity contributed by the friend circle and the data availability that can be achieved. On this basis, we propose a cloud-assisted DOSN data storage scheme Cadros, which solves the problem of low data availability caused by the limited total storage capacity of the friend circle. The protection problem improves the data availability, and theoretically proves the feasibility and validity of the Cadros scheme, establishes a real-time data availability prediction model; then studies the storage optimization problem of social data in the circle of friends, and proposes an overhead-sensitive data partitioning method and storage strategy based on the prediction results, as well as availability. Sex-driven data placement method can achieve the expected data availability, and can balance the system load and reduce the maintenance overhead of data availability. Finally, the storage optimization of social data in cloud servers is studied, and an efficient lightweight file system iFlatLFS is designed to improve the access performance of social data on cloud servers.
【學(xué)位授予單位】：國防科學(xué)技術(shù)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TP393.09;TP333

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7 楊向東;數(shù)據(jù)存儲——金融電子化的基石[J];中國金融電腦;2002年03期

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