本文選題：機會網(wǎng)絡(luò) + 協(xié)作緩存�。� 參考：《新疆大學》2014年碩士論文

【摘要】：機會網(wǎng)絡(luò)是一種不需要源節(jié)點和目標節(jié)點之間存在完整的通信鏈路，利用節(jié)點移動帶來的相遇機會實現(xiàn)數(shù)據(jù)通信的自組織網(wǎng)絡(luò)。由于機會網(wǎng)絡(luò)具有節(jié)點流動性較大、數(shù)據(jù)時延長、資源有限等特點，如何合理和高效地使用節(jié)點提供的緩存資源、增加節(jié)點間的協(xié)作來減少機會網(wǎng)絡(luò)時延、節(jié)省帶寬、防止擁塞，，最終實現(xiàn)資源共享是一個關(guān)鍵問題。 本文針對機會網(wǎng)絡(luò)中緩存空間有限的問題，深入研究了人類移動模型中節(jié)點運動狀態(tài)與相對靜止狀態(tài)下的特點，提出了基于人類移動模型的協(xié)作緩存策略，該策略利用目標地址匹配的標準來嚴格選擇協(xié)作緩存節(jié)點，并采用同步緩存數(shù)據(jù)表來達到局部域內(nèi)緩存信息共享的目的，以此能夠充分利用各個移動節(jié)點有限的緩存資源，有效提高了數(shù)據(jù)緩存命中率。由于會出現(xiàn)緩存空間已滿或數(shù)據(jù)過期的情況，因此本文提出了基于蟻群算法的緩存替換策略，該策略借鑒求解0/1背包問題的蟻群算法模型，再結(jié)合蟻群算法中信息素濃度大小，根據(jù)數(shù)據(jù)對象上信息素濃度選取數(shù)據(jù)對象，從緩存中替換出沒有選取的數(shù)據(jù)對象。 通過仿真實驗和結(jié)果分析，驗證了本文提出的協(xié)作緩存策略和緩存替換策略有效性，促進了節(jié)點間的協(xié)作，降低端到端延遲與網(wǎng)絡(luò)開銷。
[Abstract]:Opportunistic network is an ad hoc network which does not need a complete communication link between the source node and the target node and uses the encounter opportunity brought by the node movement to realize the data communication. Due to the characteristics of node mobility, extended data time and limited resources, how to use the cache resources provided by nodes reasonably and efficiently, increase the cooperation between nodes to reduce the delay of opportunity network and save bandwidth, etc. Preventing congestion and ultimately realizing resource sharing is a key problem. In order to solve the problem of limited buffer space in opportunistic networks, the characteristics of node motion state and relative static state in human mobility model are studied in this paper, and a cooperative caching strategy based on human mobility model is proposed. The strategy uses the criterion of target address matching to select the cooperative cache nodes strictly, and uses the synchronous cache data table to share the cache information in the local domain, so as to make full use of the limited cache resources of each mobile node. The data cache hit ratio is improved effectively. Because the buffer space is full or the data is out of date, a cache replacement strategy based on ant colony algorithm is proposed in this paper. The strategy uses ant colony algorithm model for solving 0 / 1 knapsack problem and combines with pheromone concentration in ant colony algorithm. The data object is selected according to the pheromone concentration on the data object, and the unselected data object is replaced from the cache. The effectiveness of the proposed cooperative cache policy and cache replacement strategy is verified by simulation experiments and results analysis. It promotes the cooperation between nodes and reduces the end-to-end delay and network overhead.
【學位授予單位】：新疆大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.06;TP18

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相關(guān)期刊論文 前2條

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