Bandwidth estimation plays an important role in characterizing Internet paths. Existing approaches can be classified into measurement tools [3],[6],[9],[10],[16],[17],[23],[29], which usually have extensive simulations, but no convergence analysis for general cross-traffic, and theoretical models [5],[14],[19],[20],[22], which usually have provable convergence, but no practical implementation. Another issue in related work is the unknown performance of certain proposed algorithms in real networks where delay measurements are not perfect due to various OS and hardware-related timing irregularities [26]. We address the former issue by developing a measurement tool PRC-MT that not only achieves asymptotic accuracy in multi-path networks with arbitrary cross-traffic, but also simultaneously measures the capacity and available bandwidth of the tight link. We address the latter issue by performing a comparison study of existing tools in Emulab and assessing their susceptibility to timing irregularities of end-hosts. Our results show that PRC-MT outperforms all existing tools in terms of accuracy, achieves similar convergence delay, and does not require any manual configuration. We also find that interrupt moderation may cause existing tools (such as Pathload [10], Pathchirp [27], and CapProbe[16]) to become quite inaccurate in certain network configurations and exhibit behavior completely different from that in ns2 [28].

In this paper, we explore multi-hop bandwidth estimation assuming arbitrary cross-traffic at each node and develop a new probing method called Envelope that can asymptotically estimate not only the available bandwidth but also the raw capacity of the tight link. Envelope is based on a multi-link recursive extension of unbiased single-hop estimators proposed in the past (e.g., [14]) and a variation of the packet-cartouche technique [6]. Through extensive simulations, we evaluate Envelope in various network settings and cross-traffic conditions and find that it can measure tight-link bandwidth characteristics with accuracy that significantly surpasses that of the existing methods. We also find that Envelope can measure non-tight links in certain path and cross-traffic configurations.

Forward-error correction (FEC) is used in many streaming applications for protecting multimedia data over lossy network paths. However, studies in the literature [1, 3, 4] report conflicting results on the benefits of FEC. To address this uncertainty, we study the performance of FEC-based streaming and provide additional insight into how FEC overhead rate affects the performance of scalable video streaming under dynamically changing network packet loss. Through analytical investigation, we derive the relationship between packet loss, FEC overhead, and utility of received video, and propose a simple control mechanism that adjusts the amount of FEC based on packet loss information. We find that our FEC control allows the application to maintain high end-user utility and achieve better quality of video at the receiver.

Video streaming is becoming an increasingly important part of the present Internet. To guarantee a high-quality streaming environment to end users, many video applications require a strict form of network QoS that is not available in the present Internet. Thus, to supplement the best-effort model of existing networks, we study a new video streaming framework that allows applications to mark their own packets with different priority and use multiqueue congestion control inside routers to effectively drop the less-important packets during buffer overflows. We describe priority AQM algorithms that provide "optimal" performance to video applications under arbitrary network loss and study a variation of Kelly's congestion control in combination with our framework. We call the combined architecture PELS - partitioned enhancement layer streaming.

In this paper, we examine the problem of estimating the capacity of bottleneck links and available bandwidth of endto -end paths under non-negligible cross-traffic conditions. We present a simple stochastic analysis of the problem in the context of a single congested node and derive several results that allow the construction of asymptotically-accurate bandwidth estimators. We first develop a generic queuing model of an Internet router and solve the estimation problem assuming renewal cross-traffic at the bottleneck link. Noticing that the renewal assumption on Internet flows is too strong, we investigate an alternative filtering solution that asymptotically converges to the desired values of the bottleneck capacity and available bandwidth under arbitrary (including non-stationary) cross-traffic. This is one of the first methods that simultaneously estimates both types of bandwidth and is provably accurate. We finish the paper by discussing the impossibility of a similar estimator for paths with two or more congested routers.

Recent research efforts to design better Internet transport protocols combined with scalable Active Queue Management (AQM) have led to significant advances in congestion control. One of the hottest topics in this area is the design of discrete congestion control algorithms that are asymptotically stable under heterogeneous feedback delay and whose control equations do not explicitly depend on the RTTs of end-flows. In this paper, we show that max-min fair congestion control methods with a stable symmetric Jacobian remain stable under arbitrary feedback delay (including heterogeneous directional delays) and that the stability condition of such methods does not involve any of the delays. To demonstrate the practicality of the obtained result, we change the original controller in Kelly's work [14] to become robust under random feedback delay and fixed constants of the control equation. We call the resulting framework Max-min Kelly Control (MKC) and show that it offers smooth sending rate, exponential convergence to efficiency, and fast convergence to fairness, all of which make it appealing for future high-speed networks.