本文選題：分布式移動社交網(wǎng)絡 + 家　； 參考：《北京交通大學》2017年碩士論文

【摘要】：互聯(lián)網(wǎng)產(chǎn)業(yè)技術(shù)的迅速發(fā)展,智能移動終端設備的大規(guī)模普及,3G、4G通信技術(shù)的廣泛應用,促進了社交網(wǎng)絡和移動終端的自然結(jié)合,分布式移動社交網(wǎng)絡應運而生。分布式移動社交網(wǎng)絡就是將人的移動性、社會性與無線通信技術(shù)相結(jié)合的一種特殊的時延容忍網(wǎng)絡。但在該網(wǎng)絡中,由于節(jié)點的移動性和間歇性連接,給信息傳輸帶來極大挑戰(zhàn)。為了促進分布式移動社交網(wǎng)絡的應用與發(fā)展,設計能反映人們真實移動規(guī)律的移動模型和高效的路由算法是特別重要的。這也是本文的主要研究內(nèi)容。為了設計一個能反映人們真實移動規(guī)律的移動模型,本文首先對Dartmouth/campus數(shù)據(jù)集進行了統(tǒng)計分析,得出在現(xiàn)實生活中,每個人在大多數(shù)的時間內(nèi)都會在幾個固定的地點之間相互轉(zhuǎn)移,而且較長時間內(nèi)這些地點是穩(wěn)定的�；诖颂匦�,本文延伸了家的概念,家不再僅指人們居住的地點,而是人們經(jīng)常訪問的地點。然后設計了一個基于家的移動模型—HBMM。在HBMM中,首先收集一段時間內(nèi)人們的移動軌跡,然后根據(jù)收集到的數(shù)據(jù)來確定人們家的集合,計算在家中的停留時間和家之間的轉(zhuǎn)移概率,最后形成馬爾可夫狀態(tài)轉(zhuǎn)移圖。狀態(tài)轉(zhuǎn)移圖中人們會以較大的概率在家的集合內(nèi)部相互轉(zhuǎn)移,以較小的概率轉(zhuǎn)移到其他不經(jīng)常訪問的區(qū)域。通過該狀態(tài)轉(zhuǎn)移圖就可以預測人們在很長一段時間內(nèi)的移動軌跡。實驗結(jié)果表明此移動模型能夠較為準確地再現(xiàn)人們實際的移動情況。為了提高分布式移動社交網(wǎng)絡中消息的轉(zhuǎn)發(fā)效率,在移動模型研究的基礎上,設計了三種基于家的多中繼路由選擇算法:HBMRZ、HBMRA和HBMR。HBMRZ中假定消息在分發(fā)階段不知道目的節(jié)點家的位置,為了提高消息的傳輸成功率,設計了該情況下的最優(yōu)化中繼選擇策略,通過該策略,可以使所有中繼節(jié)點家的覆蓋范圍最廣,從而提高消息的傳輸成功率。HBMRA中假定消息分發(fā)階段知道目的節(jié)點家的信息,該情況下我們就會選擇那些與消息目的節(jié)點家的集合相似度高的節(jié)點作為消息的中繼節(jié)點。HBMR是一種實際情況,每個節(jié)點都會建立一張類似于路由表的關于節(jié)點家的信息表,節(jié)點相遇時,會彼此交換更新信息表。當節(jié)點進行消息轉(zhuǎn)發(fā)時,就可以通過信息表獲取到消息目的節(jié)點家的信息。通過仿真實驗,也證明了這三種算法都是優(yōu)于傳統(tǒng)的多中繼選擇算法SprayWait和HS的,而且HBMRA的性能還要遠遠優(yōu)于HBMRZ,HBMR的性能趨近于HBMRA。
[Abstract]:With the rapid development of Internet technology and the wide application of 3G 4G communication technology, the distributed mobile social network emerges as the times require. Distributed mobile social network is a special delay-tolerant network which combines mobility, sociality and wireless communication technology. However, due to the mobility and intermittent connection of nodes in the network, it brings great challenges to the transmission of information. In order to promote the application and development of distributed mobile social networks, it is very important to design mobile models and efficient routing algorithms that can reflect the real movement of people. This is also the main research content of this paper. In order to design a movement model that can reflect the real movement of people, this paper firstly makes a statistical analysis of the Dartmouth/campus data set, and concludes that in real life, everyone will transfer to each other in several fixed places most of the time. And these sites are stable for a long time. Based on this feature, this paper extends the concept of home, which not only refers to the place where people live, but also the place that people often visit. Then, a home-based mobile model, HBMMM-based, is designed. In HBMM, people's moving trajectories are collected for a period of time, then the collection of people's homes is determined according to the collected data, the residence time and the transition probability between homes are calculated, and finally a Markov state transition map is formed. In the state transition graph, people will transfer to other infrequently visited areas with a high probability of transferring to each other within the set at home, and to other infrequently visited areas with a lower probability. The state transition graph can predict the trajectory of people over a long period of time. The experimental results show that the model can accurately reproduce the actual movement of people. In order to improve the efficiency of message forwarding in distributed mobile social networks, based on the research of mobile model, three home-based multi-relay routing algorithms: HBMRZ HBMRA and HBMR.HBMRZ are designed, which assume that the message does not know the location of the destination node in the distribution phase. In order to improve the success rate of message transmission, the optimal relay selection strategy is designed in this case. Through this strategy, all relay nodes can have the widest coverage. In order to improve the success rate of message transmission. HBMRA assumes that the message distribution phase knows the information of the destination node, In this case, we will select those nodes that have a high similarity to the message destination family as the relay node of the message. HBMR is a practical situation, each node will establish a similar routing table about the home of the node information table. When nodes meet, they exchange updated information tables with each other. When the node forwards the message, the information of the destination node can be obtained through the information table. The simulation results show that these three algorithms are superior to the traditional multi-relay selection algorithms (SprayWait and HS), and the performance of HBMRA is much better than that of HBMR.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN929.5;TP393.09

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