Recent studies observe that competing adaptive video streaming applications generate flows that lead to instability, under-utilization, and unfairness in bottleneck link sharing within the network. Additional measurements suggest there may also be a negative impact on users' perceived quality of service as a consequence. While it may be intuitive to resolve application-generated issues at the application layer, in this paper we explore the merits of a network layer solution. We are motivated by the observation that traditional network-layer metrics associated with throughput, loss, and delay are inadequate to the task. To bridge this gap we present a network-layer QoS framework for adaptive streaming video fairness that reflect the video user's quality of experience (QoE). We begin first by deriving a new measure to describe user-level fairness among competing flows, one that reflects the dynamics between the video encoding and its mapping to a screen with a given size and resolution. We then design and implement our framework in VHS (Video-Home-Shaper) to evaluate performance in the home's last access hop where this problem is known to exist. Experiments using a variety of devices, O/S platforms, and viewing screens demonstrate the merits of using video QoE as a basis for fair bandwidth sharing.

HTTP adaptive video streaming is an emerging technology that aims to deliver video quality to clients in a manner that accommodates available bandwidth and its fluctuations. In this scheme, a video stream is split at the server into small video files encoded at multiple bitrates. The video is composed at the client by downloading these files over HTTP and TCP. Although there are some efforts to standardize media representation for this technology, adaptation techniques remain an open area for development. Recently, an alarm was raised by a study about the interaction between TCP congestion control algorithms and large buffers on the Internet. Queuing delays when these buffers are full can reach several hundreds of milliseconds in a phenomenon that was dubbed buffer bloat. In this paper we use measurements on a testbed to demonstrate and quantify the buffer bloat effect of HTTP adaptive streaming. We show that in a typical residential setting a single video stream can easily cause queuing delays up to one second and even more hence seriously degrading the performance of other applications sharing the home network. We develop SABRE (Smooth Adaptive Bit RatE), a scheme that can be implemented by the client to mitigate this problem. We implemented SABRE in the VLC player. Using our testbed, we show that our technique can reduce buffer occupancy and significantly diminish the buffer bloat effect without affecting the experience of the video viewer.

Message Ferrying is a mobility assisted scheme in which a special node, called a message ferry, is tasked with delivering data among a set of disconnected wireless nodes. One key challenge for such scheme is to design the ferry route in a way that improves certain network characteristics such as average data delivery delay or data loss ratio. Previous work has optimized ferry travel time, rather than directly optimizing message delivery performance metrics. In this paper, we revisit the basic ferry route design problem for stationary nodes with the goal of providing a framework for optimizing delay performance. We start with a Markovian Decision Problem (MDP) formulation which produces the optimal ferry route that minimizes the average data delivery delay. While this formulation, in principle, enables optimal ferry route design, it is numerically intractable for moderate to large size problems. Solutions to small problems, however, yield insight into the properties of optimal ferry routes. These insights, in turn, lead us to propose a ferry route design algorithm that takes advantage of the similarity between our problem and the link scheduling problem in traditional networks. Our algorithm is inspired by the Deficit Round Robin (DRR) algorithm which has provable properties for delay optimization when applied to link scheduling. Using simulations we show that our DRR-based algorithm produces ferry routes that are close to optimal when compared to the MDP-derived solutions for small problems. Our results also show that our algorithm produces ferry routes for moderate to large problems that significantly outperform existing solutions.

Most commercial video streaming systems rely on Content Distribution Networks (CDNs) to distribute video content. HTTP adaptive streaming has been recently adopted by major video streaming providers and is now considered the standard technique used with CDN-based streaming systems. Despite the success of these systems, cost-effective scalability continues to be of concern in their design and deployment. To address this, recent work has proposed the use of hybrid CDN and Peer-to-peer (P2P) live streaming systems. The design of these systems aims to combine the scalability of P2P systems and the desirable performance properties of CDN-based systems. However, the use of adaptive streaming, has not been explored extensively in such hybrid systems. Designing and operating an adaptive hybrid streaming system is very challenging. Two design decisions are very critical in the operation of any such system. The first one is the bitrate adaptation strategy which specifies how different bitrates are assigned to different users while maximizing user satisfaction. The second is defining the operational guidelines for switching the system between the CDN and the P2P modes while efficiently utilizing the available resources. In this paper we present a model and analysis of a hybrid CDN-P2P adaptive live streaming system with the objective of answering these two design questions. We first present a stochastic fluid model to the hybrid streaming system with a single video bitrate and we obtain theoretical results to guide the system operation as described above. We then extend the analysis to the adaptive streaming case with multiple video bitrates. We model adaptive streaming as a linear optimization problem to obtain the best bitrate adaptation strategy. We validate our analysis using simulations. Our conclusion is that adaptive hybrid streaming can significantly improve the ability of the system to satisfy more users with higher video bitrates over CDN-based systems.

Many enterprise, campus, and data-center networks have complex layer-2 virtual LANs ("VLANs") below the IP layer. The interaction between layer-2 and IP topologies in these VLANs introduces hidden dependencies between IP level network and the physical infrastructure that has implications for network management tasks such as planning for capacity or reliability, and for fault diagnosis. This paper characterizes the extent and effect of these dependencies in a large campus network. We first present the design and implementation of EtherTrace, a tool that we make publicly available, which infers the layer-2 topology using data passively collected from Ethernet switches. Using this tool, we infer the layer-2 topology for a large campus network and compare it with the IP topology. We find that almost 70% of layer-2 edges are shared by 10 or more IP edges, and a single layer-2 edge may be shared by as many as 34 different IP edges. This sharing of layer-2 edges and switches among IP paths commonly results from trunking multiple VLANs to the same access router, or from colocation of academic departments that share layer-2 infrastructure, but have logically separate IP subnet and routers. We examine how this sharing affects the accuracy and specificity of fault diagnosis. For example, applying network tomography to the IP topology to diagnose failures caused by layer-2 devices results in only 54% accuracy, compared to 100% accuracy when our tomography algorithm takes input across layers.

In this paper we consider how vehicular networking technology can be used to support roadside-to-roadside (r2r) communications. In this form of communication vehicles traveling along a road or highway are used to transport data between two fixed roadside locations that are too far apart to be connected. The basic idea is to have a roadside station give data to a moving vehicle as it gets close and then have the vehicle carry and then deliver the data to the other roadside station. In previous work we first considered the feasibility of such a service. In this paper we aim to take concrete steps towards making the deployment of such a service real and useable. We, therefore, focus on two main aspects of such a service: 1) The design of the data transfer mechanisms between the roadside stations and the vehicles assuming a standard 802.11 MAC protocol is in use, and 2) The design of schemes to insure reliable data transfer between the two roadside stations over the particularly challenging channel provided by the moving vehicles. We describe and evaluate several schemes to achieve data transfer reliability. We find that a rateless coding scheme is best for the transfer of small to moderate files, while a hybrid ARQ/data replication scheme performs well for larger file transfers.