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篇名 |
Adaptive Caching Strategy Based on Big Data Learning in ICN
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並列篇名 | Adaptive Caching Strategy Based on Big Data Learning in ICN |
作者 | Ling Cai、Xingwei Wang、Keqin Li、Hui Cheng、Jiannong Cao |
英文摘要 | In-network caching, a typical feature of information centric networking (ICN) architecture, has played an important role on the network performance. Existing caching management strategies mainly focus on minimizing the redundancy content by exploiting either node data or content data respectively, which may not lead to effectively improve the caching performance, as there is no consideration on supplementary action of these two types of data. In this paper, the correlation between node data and content data brought by the big data are analyzed and mined to determine whether the selected content are cached in a few suitable nodes, and a Big data driven Adaptive In-network Caching management strategy (BAIC) is proposed. Driven by the current state of node and content, a novel multidimensional state attribution data model including network, node and content data is proposed. Based on the data model, the mapping relationship between the status data and the matching relationship value is further analyzed and mined. And then utilizing this mapping relationship function, the matching algorithm to predict the matching relationship between the node and the content in the next time period is proposed. The simulation experiments demonstrate that the proposed BAIC has significantly improved the network performance. |
起訖頁 | 1677-1690 |
關鍵詞 | Information centric networking、Caching、Big data learning |
刊名 | 網際網路技術學刊 |
期數 | 201811 (19:6期) |
出版單位 | 台灣學術網路管理委員會 |
DOI |
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