A Classification-Based Wisdom Caching scheme for Content Centric Networking

• Published in: 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) pp. 822 - 827
• Main Authors: Jianfeng Guan, Yunhang He, Quan Wei, Zhang Neng
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2016
• Subjects: Cache Mapping; Caching; Classification; Classification algorithms; Content Centric Networking; Correlation; Feature extraction; Mobile radio mobility management; Quality of service; Regional Correlation
• DOI: 10.1109/INFCOMW.2016.7562190

The major objective of mobility management is to achieve efficient contents transfer for mobile nodes. Content Centric Networking (CCN), as a content-oriented architecture, is designed for efficient content delivery which can easily provide mobility management based on content caching. Caching schemes of CCN deeply influences the content acquisition efficiency and whole network performance. However, the existing cache policies are relatively stiff and lack of comprehensive consideration in terms of users and contents. As a result, the performance of caching cannot dynamically adapt to the change of users' demand for content items. In this paper, we propose a Classification-Based Wisdom Caching (CBWC) scheme for CCN, which can distinguish the regional correlation of user requests and reasonably organize cache content items according to the need of users in different regions. We evaluate the CBWC scheme and the results indicate that the proposed CBWC scheme can improve the hit rate of cache and optimize the users' quality of experience, which can be further improve the performance of mobility management.