返回
Fast Content Delivery Using a Testbed-Based Information-Centric Network
DOI:10.1109/ACCESS.2021.3096042.png)
摘要
En 中文
Key requirements for a better performance of multimedia applications typically include lower latency, improved security, faster content retrieval, and adjustability to the traffic load. However, the current Internet often fails to meet the requirements due to the drawbacks of the host-oriented communication architecture. Those drawbacks can be overcome by a well-recognized networking paradigm, called Information-Centric Networking (ICN), that offers name-based and information-centric communication rather than host-oriented communication. This paradigm uses an in-network caching policy and may provide enhanced security along with user mobility. Therefore, the ICN architecture can outperform the current Internet in many aspects, including, but not limited to, content transfer time, traffic load control, mobility support, and efficient network management. Most of the existing research validating the ICN paradigm's superior performance compared to the current Internet is based on simulation. In this paper, we propose a novel ICN-based testbed, where we used several modified functions for naming, routing, and caching and developed two new functions that provide mobility support and auto-playing of the retrieved content so that the performance of the ICN network is enhanced even more in terms of content delivery time or response time. The proposed testbed architecture is based on Content-Centric Networking (CCN), a prominent branch of the ICN concept. We present the testbed development procedures and the functions in detail and demonstrate that the testbed-based architecture outperforms the current Internet architecture and the basic CCN-based environment.
Keyword:
Internet
Computer architecture
Streaming media
Software
Information-centric networking
Time factors
Security
Content-centric networking
information-centric networking
testbed development
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
没有更多内容

