本文選題：非結(jié)構(gòu)化P2P網(wǎng)絡(luò) + 資源搜索�。� 參考：《北京交通大學(xué)》2015年碩士論文

【摘要】：對(duì)等網(wǎng)絡(luò)(P2P)技術(shù)是互聯(lián)網(wǎng)的研究熱點(diǎn),普遍應(yīng)用于資源共享、協(xié)同工作及實(shí)時(shí)通訊等領(lǐng)域。非結(jié)構(gòu)化P2P網(wǎng)絡(luò)具有拓?fù)浣Y(jié)構(gòu)簡(jiǎn)單、支持模糊查詢和搜索機(jī)制容易實(shí)現(xiàn)等優(yōu)點(diǎn),得到了廣泛的應(yīng)用�，F(xiàn)有的非結(jié)構(gòu)化P2P資源搜索算法主要是基于泛洪的改進(jìn)算法及啟發(fā)式算法,這種算法主要存在兩方面問(wèn)題：(1)產(chǎn)生大量的查詢?nèi)哂喟?對(duì)網(wǎng)絡(luò)造成了一定的帶寬負(fù)擔(dān);(2)由于采用盲目搜索,搜索效率較低。針對(duì)泛洪搜索算法存在的不足,論文主要研究工作體現(xiàn)在以下兩個(gè)方面。 論文提出了基于節(jié)點(diǎn)興趣因子的資源搜索算法。該算法將Markov Chain模型應(yīng)用到資源搜索的路徑選擇問(wèn)題中,并引入節(jié)點(diǎn)興趣因子的概念,根據(jù)節(jié)點(diǎn)興趣因子確定狀態(tài)轉(zhuǎn)移概率。該算法在轉(zhuǎn)發(fā)請(qǐng)求查詢包時(shí),選擇最能發(fā)回查詢反饋包的節(jié)點(diǎn)作為下一跳,保證了隨機(jī)采樣過(guò)程能以較快的速度向目標(biāo)資源節(jié)點(diǎn)轉(zhuǎn)移,即發(fā)出請(qǐng)求節(jié)點(diǎn)能快速搜索到被請(qǐng)求資源。仿真實(shí)驗(yàn)表明,相較于傳統(tǒng)的泛洪算法,該算法用更少的搜索跳數(shù)獲得更高的資源搜索成功率。 基于節(jié)點(diǎn)興趣因子的資源搜索算法僅考慮節(jié)點(diǎn)的興趣,并未考慮網(wǎng)絡(luò)的負(fù)載均衡問(wèn)題,網(wǎng)絡(luò)中的資源搜索任務(wù)集中在部分擁有熱點(diǎn)資源的節(jié)點(diǎn)上,因此隨著資源搜索任務(wù)的增加,網(wǎng)絡(luò)將不能保證搜索性能。在前邊工作的基礎(chǔ)上,為解決負(fù)載問(wèn)題,論文引入了負(fù)載因子的概念,提出了一種結(jié)合節(jié)點(diǎn)興趣的負(fù)載均衡資源搜索算法。該算法綜合考慮了節(jié)點(diǎn)興趣及負(fù)載情況,以這兩類(lèi)轉(zhuǎn)發(fā)因子構(gòu)建Markov Chain的轉(zhuǎn)移概率矩陣,使得查詢沿著轉(zhuǎn)發(fā)因子增大的方向擴(kuò)展采樣。通過(guò)仿真實(shí)驗(yàn)表明,該算法具有較高的搜索效率和較為均衡的網(wǎng)絡(luò)負(fù)載。
[Abstract]:P2P (Peer-to-Peer Network) technology is a hot topic in Internet research. It is widely used in the fields of resource sharing, collaborative work and real-time communication.Unstructured P2P network has been widely used because of its simple topology, easy implementation of fuzzy query and search mechanism.The existing unstructured P2P resource search algorithms are mainly based on the improved flooding algorithm and heuristic algorithm. This algorithm has two main problems: 1) generate a large number of redundant query packets.Because of blind search, search efficiency is low.In view of the shortcomings of flooding search algorithm, the main research work of this paper is as follows.A resource search algorithm based on nodal interest factor is proposed in this paper.The algorithm applies the Markov Chain model to the path selection problem of resource search, and introduces the concept of nodal interest factor, and determines the state transition probability according to the nodal interest factor.When forwarding the request query packet, the algorithm selects the node most capable of sending back the query feedback packet as the next hop, which ensures that the random sampling process can transfer to the target resource node at a faster speed.That is, send the request node can quickly search the requested resources.The simulation results show that compared with the traditional flooding algorithm, the algorithm achieves a higher success rate with less search hops.The resource search algorithm based on the interest factor of nodes only considers the interests of the nodes, and does not consider the load balancing problem of the network. The resource search tasks in the network are concentrated on some nodes with hot resources.Therefore, with the increase of resource search tasks, the network will not guarantee the search performance.In order to solve the load problem, this paper introduces the concept of load factor, and proposes a load balancing resource search algorithm combined with node interest.In this algorithm, the interest and load of nodes are considered synthetically, and the transfer probability matrix of Markov Chain is constructed by using these two kinds of forwarding factors, so that the query can be sampled in the direction of increasing the forwarding factor.The simulation results show that the algorithm has high search efficiency and balanced network load.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：TP393.02

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本文編號(hào)：1768037