本文關(guān)鍵詞： 海量數(shù)據(jù)環(huán)境 大型ISP網(wǎng)絡(luò) 流量卸載　出處：《科學(xué)技術(shù)與工程》2017年13期 　論文類型：期刊論文

【摘要】：海量數(shù)據(jù)環(huán)境下大型ISP網(wǎng)絡(luò)流量爆炸性增長造成網(wǎng)絡(luò)阻塞。當(dāng)前網(wǎng)絡(luò)流量卸載方法通過預(yù)測確定待卸載網(wǎng)絡(luò)流量,卸載準(zhǔn)確率較低,服務(wù)質(zhì)量差。為此,提出一種新的海量數(shù)據(jù)環(huán)境下大型ISP網(wǎng)絡(luò)流量卸載方法,通過最大熵法,依據(jù)采集流量中的語義信息對流量類型進(jìn)行識別。依據(jù)海量數(shù)據(jù)環(huán)境下大型ISP網(wǎng)絡(luò)流量源節(jié)點的位置關(guān)系,通過圖論法確定最佳傳輸路線,實現(xiàn)對大型ISP網(wǎng)絡(luò)流量的卸載。依據(jù)中繼節(jié)點數(shù)量與總卸載時間最少原則,通過Dijkstra方法對海量數(shù)據(jù)環(huán)境下大型ISP網(wǎng)絡(luò)流量最佳卸載路線進(jìn)行求解。實驗結(jié)果表明,采用所提方法對大型ISP網(wǎng)絡(luò)流量進(jìn)行卸載,不僅流量類型識別精度高,而且卸載率高,服務(wù)質(zhì)量高。
[Abstract]:The explosive growth of large ISP network traffic in massive data environment results in network congestion. Current network traffic unloading methods determine the network traffic to be unloaded by prediction. The unload accuracy is low and the quality of service is poor. In this paper, a new method of unloading large ISP network traffic under the environment of massive data is proposed, and the maximum entropy method is adopted. According to the semantic information of the collected traffic, the traffic type is identified. According to the location relationship of the traffic source node in the large-scale ISP network under the massive data environment, the best transmission route is determined by the graph theory method. Realize the unloading of large ISP network traffic, according to the number of relay nodes and the principle of minimum total unload time. The Dijkstra method is used to solve the optimal unloading route of large scale ISP network traffic under the environment of massive data. The experimental results show that the proposed method is used to unload the large ISP network traffic. Not only the accuracy of traffic type identification is high, but also the unloading rate is high, and the quality of service is high.
【作者單位】： 百色學(xué)院信息工程學(xué)院;
【基金】：2015年廣西高校科學(xué)技術(shù)研究項目(KY2015ZD118)資助
【分類號】：TP393.06
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本文編號：1493952