【摘要】：提出了一種新的基于興趣挖掘的機(jī)會(huì)網(wǎng)絡(luò)內(nèi)容分發(fā)策略(Interest Mining Based Scheme,IMBS),通過(guò)貝葉斯理論分析節(jié)點(diǎn)的興趣以及節(jié)點(diǎn)基于興趣的相遇頻率,挖掘移動(dòng)節(jié)點(diǎn)隨機(jī)運(yùn)動(dòng)背后所蘊(yùn)含的人類社交特征和情感特征.此外,IMBS采用發(fā)布/訂閱機(jī)制,收集節(jié)點(diǎn)的訂閱信息,以獲取消息在整個(gè)網(wǎng)絡(luò)中的需求量.在轉(zhuǎn)發(fā)消息的時(shí)候,IMBS把消息的需求總量和節(jié)點(diǎn)的情感特征以及社交特征結(jié)合起來(lái)選擇下一跳節(jié)點(diǎn).仿真實(shí)驗(yàn)及算法復(fù)雜度分析表明,在不提高算法復(fù)雜度的情況下,IMBS可顯著減少消息的傳輸延時(shí)和網(wǎng)絡(luò)開銷,并提高消息傳輸?shù)某晒β?
[Abstract]:In this paper, a new opportunity network content distribution strategy based on interest mining (Interest Mining Based Scheme,IMBS) is proposed. The interest of nodes and the frequency of encounter based on interest are analyzed by Bayesian theory. Mining the human social and emotional characteristics behind the random motion of mobile nodes. In addition, IMBS uses publish / subscribe mechanism to collect the subscription information of nodes to obtain the demand of messages in the whole network. When forwarding a message, IMBS combines the total amount of message requirements with the emotional and social characteristics of the node to select the next hop node. Simulation results and algorithm complexity analysis show that IMBS can significantly reduce message transmission delay and network overhead, and improve the success rate of message transmission without increasing the complexity of the algorithm.
【作者單位】： 華南師范大學(xué)物理與電信工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(61471175) 教育部新世紀(jì)優(yōu)秀人才支持計(jì)劃項(xiàng)目(NCET-13-0805)
【分類號(hào)】：TN929.5

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