本文選題：移動(dòng)計(jì)算 + 檢查點(diǎn)技術(shù)�。� 參考：《哈爾濱工程大學(xué)》2012年碩士論文

【摘要】：與傳統(tǒng)的分布式計(jì)算相比，移動(dòng)計(jì)算系統(tǒng)具有一些固有特性，如移動(dòng)主機(jī)存儲(chǔ)空間小、能量低，無線網(wǎng)絡(luò)帶寬低以及無線連接易受干擾等。移動(dòng)計(jì)算系統(tǒng)因?yàn)檫@些固有特性容易出現(xiàn)故障，如果沒有針對(duì)移動(dòng)計(jì)算故障的有效處理機(jī)制，將影響到移動(dòng)計(jì)算系統(tǒng)正常運(yùn)行。容錯(cuò)技術(shù)是保障移動(dòng)計(jì)算系統(tǒng)正常運(yùn)行的有效手段，而檢查點(diǎn)技術(shù)又是一種常用的容錯(cuò)技術(shù)。在檢查點(diǎn)技術(shù)的應(yīng)用中涉及檢查點(diǎn)數(shù)據(jù)的存儲(chǔ)問題，檢查點(diǎn)存儲(chǔ)策略是否合理直接影響著移動(dòng)計(jì)算系統(tǒng)的性能。 本文將移動(dòng)主機(jī)進(jìn)程完成一個(gè)標(biāo)準(zhǔn)計(jì)算任務(wù)的平均時(shí)間作為衡量移動(dòng)計(jì)算系統(tǒng)性能的指標(biāo)，時(shí)間越少則表示系統(tǒng)的性能越好。經(jīng)過分析，移動(dòng)主機(jī)完成一個(gè)計(jì)算任務(wù)平均時(shí)間隨著平均額外時(shí)間開銷的增大而增大。系統(tǒng)往往在移動(dòng)主機(jī)握手遷移時(shí)對(duì)檢查點(diǎn)數(shù)據(jù)的存儲(chǔ)位置進(jìn)行調(diào)整。目前主要有三種檢查點(diǎn)存儲(chǔ)策略包括Eager策略、Lazy策略以及Trickle策略，但是它們?cè)谶w移檢查點(diǎn)時(shí)帶有盲目性，在移動(dòng)主機(jī)進(jìn)程完成一個(gè)標(biāo)準(zhǔn)計(jì)算任務(wù)過程中引入了較大的平均額外時(shí)間開銷。 本文分析比較了幾種傳統(tǒng)檢查點(diǎn)存儲(chǔ)策略的優(yōu)點(diǎn)與缺點(diǎn)，本著繼承各策略優(yōu)點(diǎn)，同時(shí)摒棄各策略缺點(diǎn)的思路，提出了基于移動(dòng)主機(jī)進(jìn)程故障概率檢查點(diǎn)存儲(chǔ)策略。該策略將移動(dòng)主機(jī)進(jìn)程運(yùn)行狀態(tài)的穩(wěn)定性作為是否進(jìn)行檢查點(diǎn)遷移的依據(jù)，避免了檢查點(diǎn)遷移的盲目性，能夠保證在所有的移動(dòng)主機(jī)進(jìn)程故障概率下都能引入較小的平均額外時(shí)間開銷，從而降低移動(dòng)主機(jī)進(jìn)程完成一個(gè)標(biāo)準(zhǔn)計(jì)算任務(wù)的平均時(shí)間。本文給出了移動(dòng)主機(jī)進(jìn)程故障概率模型，用以計(jì)算移動(dòng)主機(jī)發(fā)生握手遷移時(shí)，移動(dòng)主機(jī)進(jìn)程在下一個(gè)區(qū)域發(fā)生故障的概率，從而判定移動(dòng)主機(jī)進(jìn)程運(yùn)行狀態(tài)的穩(wěn)定性。 最后，，本文對(duì)各策略進(jìn)行了理論上的比較分析，并通過實(shí)驗(yàn)驗(yàn)證了分析結(jié)果。結(jié)果顯示基于移動(dòng)主機(jī)進(jìn)程故障概率檢查點(diǎn)存儲(chǔ)策略能夠使移動(dòng)主機(jī)進(jìn)程以更小的平均時(shí)間完成一個(gè)標(biāo)準(zhǔn)計(jì)算任務(wù)，從而提升了移動(dòng)計(jì)算系統(tǒng)的性能。
[Abstract]:Compared with the traditional distributed computing, the mobile computing system has some inherent characteristics, such as small storage space, low energy, low bandwidth of wireless network and vulnerable to interference of wireless connection. Mobile computing systems are prone to failure because of these inherent characteristics. If there is no effective mechanism to deal with mobile computing failures, it will affect the normal operation of mobile computing systems. Fault-tolerant technology is an effective means to ensure the normal operation of mobile computing system, and checkpoint technology is a commonly used fault-tolerant technology. The application of checkpoint technology involves the storage of checkpoint data. Whether the checkpoint storage strategy is reasonable or not directly affects the performance of mobile computing system. In this paper, the average time for a mobile host process to complete a standard computing task is taken as an index to measure the performance of a mobile computing system. The less the time is, the better the performance of the system is. After analysis, the average time for mobile host to complete a computing task increases with the increase of average extra time cost. The system often adjusts the storage location of checkpoint data when the mobile host handshake migrates. At present, there are three kinds of checkpointing storage strategies, including Eager policy, Lazy policy and Trickle policy, but they are blind when migrating checkpoint. In the process of mobile host process completing a standard computing task, the average extra time cost is introduced. This paper analyzes and compares the advantages and disadvantages of several traditional checkpointing storage strategies, inherits the advantages of each strategy, and at the same time abandons the ideas of the shortcomings of each strategy, and proposes a fault probability checkpoint storage strategy based on mobile host process. In this strategy, the stability of the running state of the mobile host process is taken as the basis of whether to carry out checkpoint migration, and the blindness of checkpoint migration is avoided. It can ensure that the average extra time cost is small under the failure probability of all mobile host processes, thus reducing the average time for mobile host processes to complete a standard computing task. In this paper, a fault probability model of mobile host process is presented, which is used to calculate the probability of failure of mobile host process in the next area when handshake migration occurs, so as to determine the stability of mobile host process running state. Finally, this paper makes a theoretical comparative analysis of the strategies, and verifies the results through experiments. The results show that the checkpoint storage strategy based on the fault probability of the mobile host process can make the mobile host process complete a standard computing task with a smaller average time, thus improving the performance of the mobile computing system.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TP338

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 邵志南,路林吉;分布式容錯(cuò)工業(yè)網(wǎng)絡(luò)的設(shè)計(jì)與實(shí)現(xiàn)[J];電子技術(shù)應(yīng)用;1998年12期

2 楊金民;張大方;黎文偉;;一種可靠高效的回卷恢復(fù)實(shí)現(xiàn)方法[J];電子學(xué)報(bào);2006年02期

3 門朝光;徐振朋;李香;;移動(dòng)計(jì)算系統(tǒng)檢查點(diǎn)遷移策略的性能評(píng)價(jià)[J];哈爾濱工業(yè)大學(xué)學(xué)報(bào);2010年05期

4 姚建盛;劉艷玲;;一種基于移動(dòng)計(jì)算的非阻塞協(xié)同檢查點(diǎn)算法[J];哈爾濱理工大學(xué)學(xué)報(bào);2011年02期

5 張悠慧,汪東升,鄭緯民;Windows NT環(huán)境下的進(jìn)程檢查點(diǎn)設(shè)置與回卷恢復(fù)[J];計(jì)算機(jī)研究與發(fā)展;2001年01期

6 劉媛媛;;公路車輛自動(dòng)計(jì)費(fèi)系統(tǒng)[J];長(zhǎng)春工業(yè)大學(xué)學(xué)報(bào)(自然科學(xué)版);2008年03期

7 魏曉輝,鞠九濱;分布式系統(tǒng)中的檢查點(diǎn)算法[J];計(jì)算機(jī)學(xué)報(bào);1998年04期

8 汪東升,邵明瓏;具有O(n)消息復(fù)雜度的協(xié)調(diào)檢查點(diǎn)設(shè)置算法[J];軟件學(xué)報(bào);2003年01期

9 寧葵,嚴(yán)毅;分布式計(jì)算技術(shù)發(fā)展研究[J];微機(jī)發(fā)展;2004年08期

10 梁鴻;曾科宏;;網(wǎng)格環(huán)境中檢查點(diǎn)技術(shù)的研究與實(shí)現(xiàn)[J];計(jì)算機(jī)系統(tǒng)應(yīng)用;2007年04期

相關(guān)碩士學(xué)位論文 前4條

1 姚建盛;移動(dòng)計(jì)算環(huán)境下非阻塞協(xié)同檢查點(diǎn)算法研究[D];哈爾濱工程大學(xué);2010年

2 楊天開;面向應(yīng)急物流的移動(dòng)GIS及若干關(guān)鍵技術(shù)問題的研究[D];南京航空航天大學(xué);2008年

3 徐振朋;移動(dòng)計(jì)算檢查點(diǎn)遷移處理策略的研究[D];哈爾濱工程大學(xué);2008年

4 曹劉娟;移動(dòng)環(huán)境下低開銷的非阻塞檢查點(diǎn)策略的研究[D];哈爾濱工程大學(xué);2008年

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