10539713
On optimal routing with multiple traffic matrices
Routing optimization is used to find a set of routes that minimizes cost (delay, utilization). Previous work has addressed this problem for the case of a known, static end-to-end traffic matrix. In the Internet, it is difficult to accurately estimate a traffic matrix, and the constantly changing nature of Internet traffic makes it costly to maintain optimal routing by responding to traffic changes. Thus, it is of interest to maintain a set of routes that are "good" for a number of different possible traffic scenarios. In this paper, we explore ways to find an optimal set of routes with multiple traffic matrices to minimize expected cost. We focus on two general approaches, source-destination routing and destination routing. In the case of source-destination routing, we extend existing methods with a single traffic matrix to solve the optimization problem with multiple traffic matrices: we extend the convex optimization solution methods for a single traffic matrix to the multiple traffic matrix case; we also extend the gradient-based solution methods for a single traffic matrix to the multiple traffic matrix case. However, the multiple traffic matrix case requires many more control variables. In the case of destination routing, we encounter many more differences from the single traffic matrix case. The loop-free property, which is valid for the single traffic matrix case, is no longer valid for the multiple traffic matrix case, and it is difficult to extend existing methods for a single traffic matrix to solve the optimization problem with multiple traffic matrices. We show that it is NP-complete even to determine the feasibility of multiple traffic matrices. We thus propose and evaluate a heuristic algorithm for this case.
889762
Unresponsive flows and AQM performance
Routers handle data packets from sources unresponsive to TCP's congestion avoidance feedback. We are interested in the impact these sources have on active queue management (AQM) control of long-lived TCP traffic. In this paper, we combine models of TCP/AQM dynamics with models of unresponsive traffic to analyze the effects on AQM performance.
8733679
Stochastic Fluid Theory for P2P Streaming Systems
We develop a simple stochastic fluid model that seeks to expose the fundamental characteristics and limitations of P2P streaming systems. This model accounts for many of the essential features of a P2P streaming system, including the peers' realtime demand for content, peer churn (peers joining and leaving), peers with heterogeneous upload capacity, limited infrastructure capacity, and peer buffering and playback delay. The model is tractable, providing closed-form expressions which can be used to shed insight on the fundamental behavior of P2P streaming systems. The model shows that performance is largely determined by a critical value. When the system is of moderate-to-large size, if a certain ratio of traffic loads exceeds the critical value, the system performs well; otherwise, the system performs poorly. Furthermore, large systems have better performance than small systems since they are more resilient to bandwidth fluctuations caused by peer churn. Finally, buffering can dramatically improve performance in the critical region, for both small and large systems. In particular, buffering can bring more improvement than can additional infrastructure bandwidth.
1532290
Scalable fluid models and simulations for large-scale IP networks
In this article we present a scalable model of a network of Active Queue Management (AQM) routers serving a large population of Transport Control Protocol (TCP) flows. We present efficient solution techniques that allow one to obtain the transient behavior of the average queue lengths and packet loss/mark probabilities of AQM routers, and average end-to-end throughput and latencies of TCP users. We model different versions of TCP as well as different implementations of RED Random Early Detection (RED), the most popular AQM scheme currently in use. Comparisons between the models and ns simulation show our models to be quite accurate while at the same time requiring substantially less time to solve than packet level simulations, especially when workloads and bandwidths are high.
903407
On integrating fluid models with packet simulation
Fluid models have been shown to he efficient and accurate in modelling large IP networks. However, unlike packet models, it is difficult to extract packet-level information from them. In this paper, we present a hybrid simulation method that maintains the performance advantage of fluid models while providing detailed packet level information for selected packet traffic flows. We propose two models to account for the interaction between background TCP traffic in a fluid network and foreground packet traffic of interest. The first assumes that the packet traffic poses a negligible load on the fluid network whereas the second accounts for the added load by transforming the packet traffic into fluid flows and solving the resulting enhanced fluid model. The first of these yields an efficient one pass solution algorithm whereas the second requires an additional pass to account for the packet traffic load. We establish the correctness of both approaches and present their implementation within ns-2. Comparisons between the hybrid models and a classical packet simulation show the two pass approach to be quite accurate and computationally efficient.
6965590
An information-theoretic approach to network monitoring and measurement
Network engineers and operators are faced with a number of challenges that arise in the context of network monitoring and measurement. These include: i) how much information is included in measurement traces and by how much can we compress those traces?, ii) how much information is captured by different monitoring paradigms and tools ranging from full packet header captures to flow-level captures (such as with NetFlow) to packet and byte counts (such as with SNMP)? and iii) how much joint information is included in traces collected at different points and can we take advantage of this joint information? In this paper we develop a network model and an information theoretic framework within which to address these questions. We use the model and the framework to first determine the benefits of compressing traces captured at a single monitoring point, and we outline approaches to achieve those benefits. We next consider the benefits of joint coding, or equivalently of joint compression of traces captured a different monitoring points. Finally, we examine the difference in information content when measurements are made at either the flow level or the packet/byte count level. In all of these cases, the effect of temporal and spatial correlation on the answers to the above questions is examined. Both our model and its predictions are validated against measurements taken from a large operational network.
1265218
Solving Regular Tree Grammar Based Constraints
This paper describes the precise specification, design, analysis, implementation, and measurements of an efficient algorithm for solving regular tree grammar based constraints. The particular constraints are for dead-code elimination on recursive data, but the method used for the algorithm design and complexity analysis is general and applies to other program analysis problems as well. The method is centered around Paige's finite differencing, i.e., computing expensive set expressions incrementally, and allows the algorithm to be derived and analyzed formally and implemented easily. We propose higher-level transformations that make the derived algorithm concise and allow its complexity to be analyzed accurately. Although a rough analysis shows that the worst-case time complexity is cubic in program size, an accurate analysis shows that it is linear in the number of live program points and in other parameters, including mainly the arity of data constructors and the number of selector applications into whose arguments the value constructed at a program point might flow. These parameters explain the performance of the analysis in practice. Our implementation also runs two to ten times as fast as a previous implementation of an informally designed algorithm.
5285595
Periodic Pattern Analysis under Affine Distortions Using Wallpaper Groups
In this paper, the mathematical theory of wallpaper groups is used to construct a computational tool for symmetry analysis of periodic patterns. Starting with a novel peak detection algorithm based on “regions of dominance”, an input periodic pattern can be automatically classified into one of the 17 wallpaper groups. The orbits of stabilizer subgroups within the group lead to a small set of candidate motifs that exhibit local symmetry consistent with the global symmetry of the entire pattern. We further consider affine distorted periodic patterns and show that each such pattern can be classified into a small set of symmetry groups that describe the patterns’ potential symmetries under affine transformation.
15516376
Supervised rank aggregation
This paper is concerned with rank aggregation, the task of combining the ranking results of individual rankers at meta-search. Previously, rank aggregation was performed mainly by means of unsupervised learning. To further enhance ranking accuracies, we propose employing supervised learning to perform the task, using labeled data. We refer to the approach as Supervised Rank Aggregation. We set up a general framework for conducting Supervised Rank Aggregation, in which learning is formalized an optimization which minimizes disagreements between ranking results and the labeled data. As case study, we focus on Markov Chain based rank aggregation in this paper. The optimization for Markov Chain based methods is not a convex optimization problem, however, and thus is hard to solve. We prove that we can transform the optimization problem into that of Semidefinite Programming and solve it efficiently. Experimental results on meta-searches show that Supervised Rank Aggregation can significantly outperform existing unsupervised methods.
1279751
Fast lossless multi-resolution motion estimation for scalable wavelet video coding
In this paper, we propose a fast lossless multi-resolution motion estimation algorithm in shift-invariant wavelet domain by using wavelet matching error characteristic based partial distortion elimination (MR-WMEC-PDE). Due to its multi-resolution nature, the proposed approach can be applied to scalable video coding. The proposed algorithm can achieve the same estimate accuracy as full search algorithm (FSA), while needing much less computation requirement than FSA
1463365
Approximating optimal spare capacity allocation by successive survivable routing
The design of survivable mesh based communication networks has received considerable attention in recent years. One task is to route backup paths and allocate spare capacity in the network to guarantee seamless communications services survivable to a set of failure scenarios. This is a complex multi-constraint optimization problem, called the spare capacity allocation (SCA) problem. This paper unravels the SCA problem structure using a matrix-based model, and develops a fast and efficient approximation algorithm, termed successive survivable routing (SSR). First, per-flow spare capacity sharing is captured by a spare provision matrix (SPM) method. The SPM matrix has a dimension the number of failure scenarios by the number of links. It is used by each demand to route the backup path and share spare capacity with other backup paths. Next, based on a special link metric calculated from SPM, SSR iteratively routes/updates backup paths in order to minimize the cost of total spare capacity. A backup path can be further updated as long as it is not carrying any traffic. Furthermore, the SPM method and SSR algorithm are generalized from protecting all single link failures to any arbitrary link failures such as those generated by Shared Risk Link Groups or all single node failures. Numerical results comparing several SCA algorithms show that SSR has the best trade-off between solution optimality and computation speed.