Content Distribution Networks Servers Research Articles

Controlling P2P-CDN Live Streaming Services at SDN-Enabled Multi-Access Edge Datacenters

Recognizing the shortcomings of current hybrid peer-to-peer (P2P) content-distribution network (CDN) video solutions and the potential of emerging multi-access edge datacenters, we propose a novel P2P-CDN service model that is hosted at software defined networks (SDN)-enabled multi-access edge datacenters operated by network service providers (NSP). An important feature of the proposed service architecture is that both CDN access by peers and P2P video streaming between peers within edge access networks are fully controlled by cooperation of the video content provider (VCP) and NSP to optimize video service key performance indicators (KPI). The proposed fully controlled P2P-CDN architecture with P2P group formation and chunk scheduling managed at edge datacenters reduces the load on CDN servers while overcoming quality of experience (QoE) fluctuations per flow and unfairness between multiple heterogeneous video-resolution clients over reserved access network slices. Other advantages of this service include: i) better video quality and lower delay for clients; ii) better use of edge network resources; iii) avoiding illegal, unauthorized P2P content sharing. To the best of our knowledge, there are no solutions in the literature that address P2P-CDN services managed at NSP-edge datacenters combining P2P-assisted CDN, SDN-assisted edge computing, and premium service over reserved slices. Experimental results show that the proposed P2P-CDN service deployed at SDN-enabled edge datacenters provides excellent service KPI compared to other state-of-the-art solutions.

Prefetching in Content Distribution Networks via Web Communities Identification and Outsourcing

Content distribution networks (CDNs) improve scalability and reliability, by replicating content to the "edge" of the Internet. Apart from the pure networking issues of the CDNs relevant to the establishment of the infrastructure, some very crucial data management issues must be resolved to exploit the full potential of CDNs to reduce the "last mile" latencies. A very important issue is the selection of the content to be prefetched to the CDN servers. All the approaches developed so far, assume the existence of adequate content popularity statistics to drive the prefetch decisions. Such information though, is not always available, or it is extremely volatile, turning such methods problematic. To address this issue, we develop self-adaptive techniques to select the outsourced content in a CDN infrastructure, which requires no apriori knowledge of request statistics. We identify clusters of "correlated" Web pages in a site, called Web site communities, and make these communities the basic outsourcing unit. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed techniques are very robust and effective in reducing the user-perceived latency, performing very close to an unfeasible, off-line policy, which has full knowledge of the content popularity.

Analysis of a CDN–P2P hybrid architecture for cost-effective streaming media distribution

To distribute video and audio data in real-time streaming mode, two different technologies --- Content Distribution Network (CDN) and Peer-to-Peer (P2P) --- have been proposed. However, both technologies have their own limitations: CDN servers are expensive to deploy and maintain, and consequently incur a cost for media providers and/or clients for server capacity reservation. On the other hand, a P2P-based architecture requires sufficient number of seed supplying peers to jumpstart the distribution process. Compared with a CDN server, a peer usually offers much lower out-bound streaming rate and hence multiple peers must jointly stream a media data to a requesting peer. Furthermore, it is not clear how to determine how much a peer should contribute back to the system after receiving the media data, in order to sustain the overall media distribution capacity. In this paper, we propose and analyze a novel hybrid architecture that integrates both CDN- and P2P-based streaming media distribution. The architecture is highly cost-effective: it significantly lowers the cost of CDN capacity reservation, without compromising the media quality delivered. In particular, we propose and compare different limited contribution policies for peers that request a media data, so that the streaming capacity of each peer can be exploited on a fair and limited basis. We present: (1) in-depth analysis of the proposed architecture under different contribution policies, and (2) extensive simulation results which validate the analysis. Our analytical and simulation results form a rigorous basis for the planning and dimensioning of the hybrid architecture.

Object replication strategies in content distribution networks

Recently, the Internet has witnessed the emergence of content distribution networks (CDNs). In this paper, we study the problem of optimally replicating objects in CDN servers. In our model, each Internet autonomous system (AS) is a node with finite storage capacity for replicating objects. The optimization problem is to replicate objects so that when clients fetch objects from the nearest CDN server with the requested object, the average number of ASs traversed is minimized. We formulate this problem as a combinatorial optimization problem. We show that this optimization problem is NP complete. We develop four natural heuristics and compare them numerically using real Internet topology data. We find that the best results are obtained with heuristics that have all the CDN servers cooperating in making the replication decisions. We also develop a model for studying the benefits of cooperation between nodes, which provides insight into peer-to-peer content distribution.