Matthias Wichtlhuber

An SDN-Based CDN/ISP Collaboration Architecture for Managing High-Volume Flows

The collaboration of Internet service providers (ISPs) and content distribution network (CDN) providers was shown to be beneficial for both parties in a number of recent works. Influencing CDN edge server (surrogate) selection allows the ISP to manage the rising amount of traffic emanating from CDNs to reduce the operational expenditures (OPEX) of his infrastructure, e.g., by preventing peered traffic. At the same time, including the ISPs hidden network knowledge in the surrogate selection process influences the quality of service a CDN provider can deliver positively. As a large amount of CDN traffic is video-on-demand traffic, this paper investigates the topic of CDN/ISP collaboration from a perspective of high-volume long-living flows. These types of flows are hardly manageable with state-of-the-art Dynamic Name Service (DNS)-based redirection, as a reassignment of flows during the session is difficult to achieve. Consequently, varying load of surrogates caused by flash crowds and congestion events in the ISPs network are hard to compensate. This paper presents a novel approach promoting ISP and CDN collaboration based on a minimal deployment of software-defined networking switches in the ISPs network. The approach complements standard DNS-based redirection by allowing for a migration of high-volume flows between surrogates in the backend even if the communication has state information, such as Hyper Text Transfer Protocol sessions. In addition to a proof-of-concept, the evaluation identifies factors influencing performance and shows large performance increases when compared to standard DNS-based redirection.

Can Multipath TCP save energy? A measuring and modeling study of MPTCP energy consumption

Mobile data consumption has seen a considerable rise and is predicted to further increase. This is mainly caused by mobile video consumption. A promising solution is offloading cellular traffic to WiFi. Here, Multipath TCP (MPTCP) enables a seamless user experience for handover and load balancing. However, its influence on the energy consumption of smartphones is not yet well analyzed. To this end, this paper determines the energy cost of using MPTCP for mobile constant bit rate streaming on two Nexus devices and compares it to the power consumption using single interface TCP streaming. From this, recommendations for an optimal assignment of sub-streams to interfaces are derived. The measurements indicate that using MPTCP on certain smartphones causes a 20% lower energy expense compared to the cost of both interfaces individually. However, MPTCP using multiple interfaces should only be used if the requested data rate cannot be supported by a single interface.

Impact of WiFi offloading on video streaming QoE in urban environments

Video streaming is the most popular application in todays mobile Internet and its growing demands and popularity put more and more load on cellular networks. In a recent trend to mitigate the cellular load, followed by many providers, users are offered to offload mobile connections to WiFi hotspots, which are predominately deployed in urban environments. In this work, we conduct a simulative performance evaluation of the impact of WiFi offloading on the Quality of Experience (QoE) of video streaming. The evaluation is based on connectivity measurements from a German city and uses a simple QoE model for estimating the perceived quality of video streaming. Our findings show that, despite its benefits for operators, offloading to WiFi has a negative impact on video streaming QoE for some users when 3G/4G coverage is available. Only in the case of 2G coverage, WiFi offloading can significantly improve the perceived quality for users.

Parallel implementation of a real-time high dynamic range video system

This article describes the use of the parallel processing capabilities of a graphics chip to increase the processing speed of a high dynamic range HDR video system. The basis is an existing HDR video system that produces each frame from a sequence of regular images taken in quick succession under varying exposure settings. The image sequence is processed in a pipeline consisting of: shutter speeds selection, capturing, color space conversion, image registration, HDR stitching, and tone mapping. This article identifies bottlenecks in the pipeline and describes modifications to the algorithms that are necessary to enable parallel processing. Time-critical steps are processed on a graphics processing unit GPU. The resulting processing time is evaluated and compared to the original sequential code. The creation of an HDR video frame is sped up by a factor of 15 on the average.

RT-VQM: real-time video quality assessment for adaptive video streaming using GPUs

Adaptive streaming systems gain rising relevance for streaming services. Therefore, the same video is offered in multiple quality versions to clients for adaptation during playback. However, optimizing adaptation in a Quality of Experience (QoE) centric way is difficult. Current systems maximize bit rate, ignoring that different types of adaptation (resolution, framerate, quantization) correlate differently and in a non-linear way with users perception. User validated video quality metrics can provide precise quality information. However, measurements of state-of-the-art metrics show either high computational intensity or weak correlation with subjective tests. This makes large-scale offline quality assessment processing intensive while real-time constrained scenarios like live streaming and video conferencing are hardly supportable. Consequently, this work presents the Real-Time Video Quality Metric (RT-VQM), a real-time, Graphics Processing Unit (GPU) supported version of the widely used Video Quality Metric (VQM). RT-VQM introduces efficient filtering operations, hardware-supported scaling and high-performance feature pooling. The approach outperforms VQM by a factor of 30, thus enabling a real-time assessment of up to 9 parallel video stream representations up to High Definition (HD) 720 resolution at 30fps.

QTrade: a quality of experience based peercasting trading scheme

Video streaming constitutes the dominant portion of todays traffic on the Internet and will grow in the coming years. In order to provide for a low cost distribution of bulky video content, Peer-to-Peer (P2P) approaches are a viable way to cut down server bandwidth cost by utilizing users upstream bandwidth to redistribute data. However, users need an incentive to participate in such a system. The related work on incentive schemes has focused on using bandwidth contribution as a measure for contribution to the systems performance, ignoring that user perceived Quality of Experience (QoE) is not necessarily maximized by maximizing bandwidth, but by delivering the right data in the right order. Consequently, this work presents QTrade, a topology agnostic incentive scheme for adaptive P2P video streaming systems based on user-validated video quality metrics. QTrade is evaluated on top of an existing adaptive streaming overlay. The results show that QTrade utilizes bandwidth more efficiently by providing incentive to distribute parts of the video with a high QoE. Moreover, up to 70% less and shorter rebuffering events are observed for cooperative peers while maintaining a 10 to 11 times worse performance in terms of rebuffering events for non-cooperative peers.

Energy Considerations for WiFi Offloading of Video Streaming

The load on cellular networks is constantly increasing. Especially video streaming applications, whose demands and requirements keep growing, put high loads on cellular networks. A solution to mitigate the cellular load in urban environments is offloading mobile connections to WiFi access points, which is followed by many providers recently. Because of the large number of mobile users and devices there is also a high potential to save energy by WiFi offloading. In this work, we develop a model to assess the energy consumption of mobile devices during video sessions. We evaluate the potential of WiFi offloading in an urban environment and the implications of offloading connections on energy consumption of mobile devices. Our results show that, although WiFi is more energy efficient than 3G and 4G for equal data rates, the energy consumption increases with the amount of connections offloaded to WiFi, due to poor data rates obtained for WiFi in the streets. This suggests further deployment of WiFi access points or WiFi sharing incentives to increase data rates for WiFi and energy efficiency of mobile access.

Computation offloading in wireless multi-hop networks: Energy Minimization via multi-dimensional knapsack problem

Computation offloading is an upcoming approach to increase battery life of mobile devices overburdened by resource-consuming applications. In multi-hop networks, computation offloading poses new challenges since intermediate devices are required to relay tasks of others along the path to the server. The decision of a device about whether to offload or not depends thus on the provided energy of relay devices and on the decisions of other offloading devices since relay resources need to be shared. This also implies that for energy minimization, optimal decisions are topology-dependent. This paper introduces a novel theoretical framework for energy minimization of computation offloading in multi-hop wireless networks which formulates the energy minimization problem as a binary linear problem. Proving its equivalence to a multi-dimensional knapsack problem allows us to specify a greedy heuristic, which shows very good performance, with a maximal deviation of less than 5% from the optimal results. From simulations and analytical results for different topologies, we derive under which conditions computation offloading in multi-hop networks is beneficial.

How to adapt: SVC-based quality adaptation for hybrid peercasting systems

Live streaming of large-scale events such as the Olympic Games with a huge number of viewers is challenging, as the streaming infrastructure needs to scale fast and big, and often in an unpredictable manner. Peer-to-peer (P2P) live streaming (Peercasting) has proven to be beneficial in these scenarios, as resources are scaling inherently with the number of nodes. However, churn behavior in a nodes neighborhood may result in fluctuating downstream bandwidth and thus freezing (stalling) playback. Related work tries to mitigate this effect by using layered video codecs, focusing on single-dimensional scalability in mesh-pull based systems. Yet, the benefits of multidimensional scalability (resolution, frame rate, and quantization) combined with coexisting pull-/push mechanisms introduced by modern hybrid P2P streaming architectures have not been studied in detail. Consequently, this work proposes a new scheduling algorithm taking these aspects into account. The evaluation shows large benefits for end-users by reducing the frequency of stalls by 90% even under extreme conditions.

vINCENT: An incentive scheme supporting heterogeneity in Peer-to-Peer content distribution

Peer-to-Peer (P2P) has proven to be a scalable approach for content distribution, while reducing the load for the content provider. As P2P systems depend on each nodes participation, reciprocal incentive mechanisms for stimulating contribution are a major building block in those systems. However, reciprocal incentive schemes fall short for resource-poor devices, as they lead to service degradation for those nodes. This paper presents vINCENT, an incentive scheme allowing resource-poor devices to seek support from resource-rich devices. The novel scheme is based on virtual nodes which form a trusted domain around multiple devices. vINCENT has been implemented and evaluated in a P2P live streaming scenario. The solution provides good playback quality to all devices within a virtual node, given a sufficient contribution of the virtual node as a whole. At the same time, free riding nodes are isolated efficiently and the game theoretic properties of reciprocity are preserved.