Internet route survey systems such as Ark and IPRS have typically been evaluated on how well they uncover internet topology (nodes and links from consecutive traceroutehops). We present a new metric, the forwarding score, better adapted to assessing how these systems capture routing behavior, and compare this metric over eight days' data.

The EdgeNet software is free, open-source, liberally licensed code that extends the Kubernetes container orchestration system to the edge cloud. We use this code to run the EdgeNet testbed, an internet-scale edge cloud for distributed systems researchers. This demonstration showcases three features of EdgeNet: its multitenancy model, its multi-provider aspect, and its geographically-based selective deployment capability. Multitenancy allows multiple teams to use the platform concurrently; being multi-provider, independent contributors can make nodes available to the platform; and selective deployment facilitates location-based placement of software. Under our guidance, demo participants invoke the Kubernetes command-line interface to use the testbed. In so doing, they get experience with the testbed, which they can continue to use afterwards. They also gain insight into how the demonstrated features are useful for edge cloud container deployment in general. Participants who volunteer to help EdgeNet nodes receive Odroid devices to host in their homes or workplaces.

To satisfy the need for ubiquitous connectivity of their customers, many enterprises (e.g., hotels, cafes and commercial centers) deploy EWLAN (Enterprise WLAN). In these networks, video streaming is both one of the most popular and challenging applications. To improve the overall users QoE in EWLAN, we propose to address simultaneously the resource bottlenecks that can occur on wireless links as well as the lack of overall bandwidth that can be experienced on the Internet access link. We propose a dynamic video Streaming Management based on software defined enterprIse wireLEss LANs (SMILE), an SDN framework which dynamically allocates the bandwidth among different access points based on their workloads and on the available bandwidth. We evaluate SMILE over several adaptive video streaming performance metrics: instability, rebuffering, and average video quality. The results demonstrate an improvement for these parameters with different adaptation logics when SMILE is in use.

Dynamic Adaptive Streaming over HTTP (DASH) was introduced to enable high video quality streaming over HTTP. DASH depends on the adaptation logic at the client to choose which video bitrate to stream from the content server for each chunk. For clients receiving video over a cellular network, the cellular first hop tends to be the bandwidth bottleneck and can exhibit significant swings in available bandwidth. In this paper we develop and evaluate a Dynamic Adaptation for mobile Video Streaming (DAVS), a technique that can be used within DASH adaptation to handle the significant bandwidth variability experienced by cellular mobile clients. In our scheme the main innovation is that the client chooses a bitrate based on whether the playout buffer occupancy (BO) falls below or above a dynamic threshold. In addition, the scheme attempts to minimize bitrate switching by again delaying a change of video bitrate selection by a window of time - that is also dynamically determined. We evaluate the performance of DAVS over real traces collected from a mobile network operator. DAVS shows better performance over different video streaming metrics. Furthermore, It increases the QoE by a range 15% - 55% compared to benchmark algorithms.

Nowadays, Internet video is the dominant internet traffic. DASH is an adaptive video streaming technique introduced to enable high quality video delivery over HTTP. In home networks, multiple video streams will compete for bandwidth, thus leading to poor performance and impacting the received quality of experience. In this paper we introduce a new technique to address this issue at the home network gateway without modifying neither the client player nor the video server. We design our framework NAVS (Network Assisted Video Streaming) relies on the deployment of Software Defined Networking (SDN). NAVS performs a dynamic traffic shaping based on the collected network traffic statistics and monitoring of video flows. NAVS dynamically allocates bandwidth for each video flow in real time. NAVS scheme has been evaluated over several metrics: bandwidth utilization, instability of players as well as the average video quality received by the clients. Our results demonstrate an improvement for all these parameters.

After being the support of the data and voice convergence, the Internet has become one of the main video providers such as TV-stream. As an alternative to limited or expensive technologies, P2PTV has turned out to be a promising support for such applications. This infrastructure strongly relies on the overlay composed by the peers that consume and diffuse video contents at the same time. Understanding the dynamical properties of this overlay, and in particular how the users switch from one overlay to another, appears to be a key aspect if one wants to improve the quality of P2PTV. In this paper, we investigate the question of relying on non-invasive measurement techniques to track the presence of users on several channels of P2PTV. Using two datasets obtained by using network measurement on P2PTV infrastructure, we show that such an approach contains sufficient information to track the presence of users on several channels. Besides, exploiting the view provided by sliding time windows, we are able to refine the analysis and track users that switch from one channel to another, leading to the detection of super-peers and providing explanations of the different roles they can play in the infrastructure. In addition, by comparing the results obtained on the two datasets, we show how such analyses can shed some light on the evolution of the infrastructure policy.

Adaptive video streaming techniques were introduced to enable high quality video delivery over HTTP. These schemes propose to choose dynamically the appropriate video rate to match the operating conditions. In home networks, wireless access is the predominant Internet access. Multiple clients/players with different link qualities compete over a limited wireless bandwidth to transfer their video streams. As a result, some users undergo unpredictable degradations of their Quality of Experience (QoE) while others benefit from these perturbations. In this paper we introduce a new technique to address this issue at the gateway without modifying neither the client nor the video server side. We design a framework WNAVS (Wireless Network Assisted Video Streaming) that relies on the deployment of Software Defined Networking (SDN). WNAVS performs a dynamic traffic shaping based on collected network traffic statistics and allocates bandwidth for the clients in real time. We evaluate WNAVS over several metrics: fairness, instability, average video quality as well as the video traffic utilization. Our results demonstrate an improvement for all these parameters.

Recently, most peer-to-peer (P2P) applications ignore traffic costs at internet service providers (ISPs), and thus generate a large amount of traffic crossing ISPs or autonomous systems (ASes) on the Internet. To reduce the cross-ISP/AS traffic, the existing approaches introduce network-aware strategies in which a lot of modifications of P2P systems are required. In this paper, we propose a router-aided method for localizing P2P traffic hierarchically with multiple levels. By intentionally limiting the bandwidth of each connection path between peers based on geographical location of the peers' destinations, the traffic can be localized. Compared to the existing locality-enhancing approaches, our proposed method does not require dedicated servers, cooperation between ISPs and users, or any modification of existing P2P application software. Therefore, the proposal can be easily utilized by all types of P2P applications. The experimental results obtained with P2P streaming applications show that our proposed method not only successfully realizes traffic localization but also maintains a good performance of P2P applications.

Recently, peer-to-peer (P2P) traffic is increasing rapidly in volume day by day. One of the main causes is that most of P2P applications including file sharing and streaming applications often form overlay networks for exchanging data that are oblivious to the underlay network topology. As a result, they generate a large amount of inter-domain traffic causing higher cost for Internet service providers (ISPs). This raises a problem of traffic localization. To optimize the cross-ISP/AS traffic, existing approaches focus on solving the problem on the application layer where each P2P application must be equipped with an additional protocol to obtain underlay network information from an “Oracle” server or an additional locality-aware procedure to estimate location by itself. Therefore some modifications of application software are required for these approaches. In this paper, we propose a novel solution for addressing the problem, called PLS, forcing packet loss to each P2P packet based on geographical location of each destination at the network layer. Since PLS is implemented at a network router, no software modification is required. This proposal can be applied to all types of P2P applications in order to localize the traffic. The experiment in this study evaluated on popular P2P streaming applications show that our proposed method significantly improves the performance of traffic localization problem.

Recently, peer-to-peer has been becoming a promising architecture for developing video streaming services because it can reduce the bottlenecks and the load at the server side. However, P2P systems implement their own routing protocols on overlay networks, which are largely independent of the Internet routing. As a result, the traffic generated by P2P systems is immense and unpredictable. Controlling the P2P traffic is therefore becoming a big challenge for internet service providers (ISPs). Considering the P2P traffic localization is one of the most efficient solutions to optimize the traffic. The existing approaches, however, require several modifications of the application software. In this paper, we propose a novel traffic localization method for P2P streaming application (P2PTV) by deep packet inspection. Based on the peer list and the geographical location of the listed peers, we propose two mechanisms for localizing the traffic: the modification of the peer list packets and the redirection of the video request packets at network routers. Since our method is implemented on the network routers, it can be applied for all P2P applications without any software modifications. The experiments evaluated on a popular P2PTV, namely PPStream, prove the effectiveness of our proposed method on the problem of traffic localization.

In this paper, we present our P2P-TV measurement experiment performed in France and Japan. By using multiple measurement points in different locations of the world, we are able to get a global view of the measured P2P networks and we can infer their main properties. More precisely, we focus on the level of collaboration between peers, their location and the effect of the traffic on the networks. Our results show that there is no fairness between peers and it is an important issue for the scalability of P2P-TV systems. Moreover, hundreds of Autonomous Systems are involved in the P2P-TV traffic and it points out the lack of locality-aware mechanisms for these systems. The geographic location of peers testifies the wide spread of these applications in Asia and highlights their worldwide usage.

In this paper, we present our P2P-TV measurement experiment performed in France and in Japan. By using multiple measurement points in different locations of the world, we are able to get a global view of the measured P2P networks and we can infer their main properties. More precisely, we focus on the location of peers and the effect of the P2P-TV traffic on the networks. Our results shows that hundred of Autonomous Systems are involved in the exchange of traffic between peers and it points out the lack of locality-aware mechanisms for these P2P-TV systems. We also investigate the geographic location of users. It testifies the wide spread of these applications in Asia and highlights the worldwide usage of these applications.

Incentive mechanisms are essential components of peer-to-peer systems for file sharing such as BitTorrent, since they enforce peers to share their resources and to participate. Recent P2P systems that distribute live multimedia streams take their inspiration from BitTorrent, but have not defined incentive mechanisms appropriate to the nature of continuous media. In this article, we uncover the way that the incentive mechanisms in BitTorrent are not well suited to streaming live multimedia, and based on P2P systems that we have measured, we propose a new incentive mechanism designed for distribution of live multimedia streaming over a P2P network.

P2P IPTV applications arise on the Internet and will be massively used in the future. It is expected that P2P IPTV will contribute to increase the overall Internet traffic. Moreover, these emerging applications are proprietary and their exact implementation details are still widely unknown. In this context, it is important to measure the traffic generated by these applications to understand their underlying mechanisms and to evaluate their impact on the network.

International audience