本文選題：機會網絡 + 親密程度�。� 參考：《南京郵電大學》2017年碩士論文

【摘要】：近年來,移動通信已經逐漸成為一種人們在移動中隨時共享信息和獲取服務的重要方式。傳統(tǒng)無線通信方式是借助一定的基礎設施(如基站)來保障通信節(jié)點之間的連通性來完成通信的,但是在一些無法部署基礎設施的惡劣環(huán)境,傳統(tǒng)無線通信方式就會失效。為了解決此問題,一種新型的網絡移動機會網絡(Mobile Opportunistic Networks,MON)應運而生。MON中節(jié)點位置和網絡規(guī)模頻繁變化,端到端通信不需要確定是否存在通路,而是利用節(jié)點移動創(chuàng)造的相遇機會完成通信,因此它能夠解決間斷網絡的通信難題,具有廣闊的應用前景。但是拓撲結構的復雜多變、路由信息的缺乏等問題給MON的數據轉發(fā)帶來技術上的挑戰(zhàn),而機會路由算法可以通過對節(jié)點移動規(guī)律進行預測,使數據最大限度地轉發(fā)至目的節(jié)點。一般地,對節(jié)點歷史軌跡信息進行分析可以在一定程度上幫助預測節(jié)點的移動規(guī)律,此外由人攜帶的設備組成的MON還可以利用節(jié)點移動的社會屬性來預測節(jié)點移動規(guī)律從而達到提高預測精度的目的。本文主要研究如何利用節(jié)點移動的社會屬性來提高機會路由算法性能�；谏鐣䦟傩缘臋C會路由算法通常考慮的社會屬性包括節(jié)點所屬社區(qū)、節(jié)點親密性、節(jié)點社會地位等。其中在利用親密性預測節(jié)點接觸概率的機會路由算法中,節(jié)點親密性評價的準確性會影響節(jié)點接觸概率預測的精度,進而影響機會路由算法的性能,因此應該全面分析與節(jié)點親密性相關的各個因素,建立數學模型描述并整合各因素,期望能夠準確地評價節(jié)點之間的親密程度并設計相應的機會轉發(fā)策略�，F有的研究在評價節(jié)點親密性時一般沒有考慮節(jié)點位置影響。實際上,節(jié)點在不同區(qū)域其親密節(jié)點也會不同。本文綜合考慮了節(jié)點親密性的時間相關性和區(qū)域相關性,利用節(jié)點的歷史接觸信息來構造節(jié)點親密程度的評價模型,從而得到節(jié)點在相應區(qū)域的親密節(jié)點作為其區(qū)域朋友,最后結合節(jié)點當前位置和區(qū)域朋友關系提出一種基于區(qū)域朋友關系的機會路由算法(Opportunistic Routing Algorithm Based on Regional Friendship,ORRF)。實驗數據表明,在不同的節(jié)點分布密度和可容忍時延下,該算法均得到較高的數據送達率和較低的轉發(fā)能耗。在本文的最后,設計實現了一個基于Wi-Fi P2P技術的可以進行點對點通信的機會網絡Android原型系統(tǒng),該系統(tǒng)具有周圍節(jié)點搜索、與周圍節(jié)點建立連接并進行數據傳輸的功能。最終運行演示機會網絡原型系統(tǒng),收集相關性能數據,為未來機會網絡的研究提供數據支持。
[Abstract]:In recent years, mobile communication has become an important way for people to share information and access services at any time. The traditional wireless communication mode is based on certain infrastructure (such as base station) to ensure the connectivity between communication nodes to complete the communication, but in some bad environment where infrastructure can not be deployed, the traditional wireless communication mode will fail. In order to solve this problem, a new mobile opportunity network, Mobile Opportunistic Networks (mon), emerges as the times require. The node location and network size change frequently in mon, and end-to-end communication does not need to determine whether there is a path or not. Instead, it makes use of the encounter opportunity created by node movement to complete communication, so it can solve the communication problem of discontinuous network and has a broad application prospect. However, the complexity of topology and the lack of routing information bring technical challenges to the data forwarding of MON, and the opportunistic routing algorithm can make the data forward to the destination node to the maximum extent by predicting the law of node movement. Generally speaking, analyzing the historical track information of nodes can help to predict the movement law of nodes to some extent. In addition, the MON, which is composed of human devices, can also use the social attributes of node movement to predict the law of node movement so as to achieve the purpose of improving the prediction accuracy. This paper mainly studies how to improve the performance of opportunistic routing algorithm by using the social attributes of node movement. Opportunistic routing algorithms based on social attributes usually consider the social attributes including the community to which the nodes belong, the intimacy of the nodes, the social status of the nodes, and so on. In the opportunistic routing algorithm which uses closeness to predict node contact probability, the accuracy of node closeness evaluation will affect the accuracy of node contact probability prediction, and then affect the performance of opportunistic routing algorithm. Therefore, all factors related to node closeness should be comprehensively analyzed, and mathematical models should be established to describe and integrate the factors, in order to accurately evaluate the degree of closeness between nodes and design corresponding opportunity forwarding strategies. Existing studies generally do not consider node location when evaluating node closeness. In fact, nodes in different regions have different intimate nodes. In this paper, the temporal and regional correlation of node closeness is considered synthetically, and the evaluation model of node closeness is constructed by using the historical contact information of nodes, and the intimate nodes in the corresponding region are obtained as their regional friends. Finally, an opportunity routing algorithm based on regional friendships is proposed, which combines the current location of nodes and regional friendships. Experimental data show that the proposed algorithm can achieve higher data delivery rate and lower forwarding energy consumption under different node distribution density and tolerance delay. At the end of this paper, an opportunistic network Android prototype system based on Wi-Fi P2P technology is designed and implemented. The system has the function of searching the surrounding nodes, establishing connections with the surrounding nodes and transmitting data. Finally, the prototype system of demo opportunity network is run, and relevant performance data are collected to provide data support for future research of opportunity network.
【學位授予單位】：南京郵電大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN929.5

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本文編號：1885727