Performance evaluation and improvement of large-scale Content-Centric Networking

Abstract

In this paper, we investigate the scalability of CCNx, open-source CCN (Content-Centric Networking) implementation, in terms of the number of nodes. As performance metrics, we measure the total throughput of content deliveries, the packet loss ratio in the network, and the average content delivery time. We also examine the performance bottleneck of CCNx through system-wide profiling, which quantitatively shows that per-packet digest-based authentication is the performance bottleneck in CCNx. Our findings include that the communication performance was degraded when the number of CCN routers exceeds 30–40, and that the Data-chunck digest computation consumes approximately 20% of the total CPU time. We therefore investigate how the scalability of CCNx in terms of the number of nodes can be improved by hardware offloading of Data-chunk digest computation. We found that hardware offloading of Data-chunk digest computation significantly reduces the average content delivery time.

DOI: 10.1109/ICOIN.2017.7899485

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Cite this paper

@article{Nakamura2017PerformanceEA, title={Performance evaluation and improvement of large-scale Content-Centric Networking}, author={Ryo Nakamura and Hiroyuki Ohsaki}, journal={2017 International Conference on Information Networking (ICOIN)}, year={2017}, pages={103-108} }