Performance Evaluation of Information-Centric Networking for Multimedia Services

Performance Evaluation of Information-Centric Networking for Multimedia Services
复制标题

DOI:
10.1109/sose.2016.52
复制
发表时间:
2016-03
期刊:
2016 IEEE Symposium on Service-Oriented System Engineering (SOSE)
影响因子:
--
通讯作者:
Haozhe Wang;G. Min;Jia Hu;W. Miao;N. Georgalas
Haozhe Wang;G. Min;Jia Hu;W. Miao;N. Georgalas
中科院分区:
其他
文献类型:
--
作者:
Haozhe Wang;G. Min;Jia Hu;W. Miao;N. Georgalas

文献摘要

被引文献

相似文献

多媒体业务的迅速发展使当前互联网的主要功能从以主机为中心的通信转向以服务为导向的内容传播。在这一重大变化的推动下,以信息为中心的网络(ICN)作为一种新的网络范式出现,其目的是为Internet上有效的信息检索提供自然支持。作为ICN的一个重要特征,网络内缓存使用户能够有效地从无处不在的缓存中访问流行内容,从而提高体验质量(QoE)。因此,近年来,ICN的网内缓存受到了广泛的关注,并提出了许多缓存方案和模型。然而,对于任意拓扑和具有突发性质的多媒体服务等实际环境下的ICN缓存模型,目前还缺乏研究。为了弥补这一差距,本文提出了一个新的分析模型,以获得对具有任意拓扑和突发内容请求的ICN缓存性能的有价值的见解。通过与仿真实验结果的比较,验证了模型的准确性。然后将分析模型用作一种经济有效的工具来研究关键网络和内容参数对ICN中缓存性能的影响。
The rapid development in multimedia services has shifted the major function of the current Internet from host-centric communication to service-oriented content dissemination. Motivated by this significant change, Information-Centric Networking (ICN) has emerged as a new networking paradigm, which aims at providing natural support for efficient information retrieval over the Internet. As a crucial characteristic of ICN, in-network caching enables users to efficiently access popular content from ubiquitous caches to improve the Quality-of-Experience (QoE). Therefore, in-network caching for ICN has received considerable attention in recent years and many cache schemes and models have been proposed. However, there is a lack of research into ICN cache models under practical environments such as arbitrary topology and multimedia services exhibiting bursty nature. To bridge the gap, this paper proposes a new analytical model to gain valuable insight into the caching performance of ICN with arbitrary topology and bursty content requests. The accuracy of the proposed model is validated by comparing the analytical results with those obtained from simulation experiments. The analytical model is then used as a cost-efficient tool to investigate the impact of key network and content parameters on the performance of caching in ICN.