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.
13098192
On the impact of concurrent downloads
Concurrent downloads accelerate information access speed for individual Web users. The speed-up comes from multiple connections launched for one subject download, which leads to unfairness at user level. We study the impact of concurrent downloads on the network. Particularly, we investigate the fairness between users who employ different downloading concurrency. We also discuss how concurrent downloads affect the transient behavior of the network.
1409797
On the TCP-Friendliness of VoIP Traffic
Recently, some concerns have been raised regarding whether the rapid growth of the UDP traffic due to the Skype-like applications will throttle down regular TCP users because UDP flows are unresponsive to network congestion, i.e., UDP senders do not reduce their sending rates when congestion occurs in the network. However, most UDP based real time applications, such as Voiceover-IP (VoIP), drop out completely if the user perceived quality becomes unacceptable as the network congestion increases. This user back-off mechanism effectively reduces UDP traffic rate at the aggregated level when the network is congested. In this paper, we investigate the fairness issue between VoIP flows and TCP flows under different network environment. Our study explicitly takes into account both transport layer congestion control mechanism built-into TCP protocol stack and the self-adaptiveness of VoIP users. Various models are developed to characterize VoIP user back-off behaviors in response to call quality degradation resulted from packet loss and delay inside the network. The comparison between VoIP user back-off and TCP rate adaption shows that not only VoIP flows consume much less bandwidth than TCP flows, but also VoIP traffic is indeed very responsive to congestion when the network is overloaded.
15563828
Self-similarity and long range dependence on the internet: a second look at the evidence, origins and implications
In this paper we critically reexamine some of the long standing beliefs regarding self-similarity and long range dependence (LRD) on the Internet. Power law tails have been conjectured to be a cause of LRD. In this paper, we reexamine the claims regarding heavy tails. We first examine the generative models for the heavy tail phenomena, both in terms of the fragility of some proposed mechanisms to modeling perturbations as well as the weak statistical evidence for the mechanisms. Next, we take a look at some of the implications of LRD in key performance aspects of Internet algorithms. Finally, we present an alternative model explaining the LRD phenomena of Internet traffic. We argue that the multiple time-scale nature of the generation of traffic and transport protocols make the observation of LRD inevitable.
12544972
Fluid models and solutions for large-scale IP networks
In this paper we present a scalable model of a network of Active Queue Management (AQM) routers serving a large population of TCP flows. We present efficient solution techniques that allow one to obtain the transient behavior of the average queue lengths, packet loss probabilities, and average end-to-end latencies. We model different versions of TCP as well as different versions of RED, the most popular AQM scheme currently in use. Comparisons between our models and <tt>ns</tt> simulation show our models to be quite accurate while at the same time requiring substantially less time to solve, especially when workloads and bandwidths are high.
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.
5064803
Body Localization in Still Images Using Hierarchical Models and Hybrid Search
We present a 3-level hierarchical model for localizing human bodies in still images from arbitrary viewpoints. We first fit a simple tree-structured model defined on a small landmark set along the body contours by Dynamic Programming (DP). The output is a series of proposal maps that encode the probabilities of partial body configurations. Next, we fit a mixture of view-dependent models by Sequential Monte Carlo (SMC), which handles self-occlusion, anthropometric constraints, and large viewpoint changes. DP and SMC are designed to search in opposite directions such that the DP proposals are utilized effectively to initialize and guide the SMC inference. This hybrid strategy of combining deterministic and stochastic search ensures both the robustness and efficiency of DP, and the accuracy of SMC. Finally, we fit an expanded mixture model with increased landmark density through local optimization. The model hierarchy is trained on a large number of gait images. Extensive tests on cluttered images with varying poses including walking, dancing and various types of sports activities demonstrate the feasibility of the proposed approach.
30364080
A flexible embedded SRAM compiler
SRAM compiler uses predefined building blocks or leaf cells and connectivity information to compile SRAMs of user-specified size. In this paper, a high-speed embedded SRAM compiler is described. It is based on TSMC's 0.5 /spl mu/m CMOS process. It can compile both single-port and dual-port SRAMs. SRAM is a completely synchronous architecture with a maximal capacity 16k/spl times/64=1 Mb bits. The compiler generates the layout, behavioral level models, schematic symbols, and a layout abstraction to place and route. The program in Skill language can automatically complete the creation of all the models in different levels. The SRAM compiler has a friendly user interface. Users can specify the necessary parameters and then get all the results. The SRAM compiler can be easily integrated into Cadence and other CAD frameworks.
10859249
Making use of population information in evolutionary artificial neural networks
This paper is concerned with the simultaneous evolution of artificial neural network (ANN) architectures and weights. The current practice in evolving ANN's is to choose the best ANN in the last generation as the final result. This paper proposes a different approach to form the final result by combining all the individuals in the last generation in order to make best use of all the information contained in the whole population. This approach regards a population of ANN's as an ensemble and uses a combination method to integrate them. Although there has been some work on integrating ANN modules, little has been done in evolutionary learning to make best use of its population information. Four linear combination methods have been investigated in this paper to illustrate our ideas. Three real-world data sets have been used in our experimental studies, which show that the recursive least-square (RLS) algorithm always produces an integrated system that outperforms the best individual. The results confirm that a population contains more information than a single individual. Evolutionary learning should exploit such information to improve generalization of learned systems.
10742303
Stability and sensitivity for congestion control in wireless networks with time varying link capacities
While extensive efforts have been devoted to providing optimization based, distributed congestion control schemes for efficient bandwidth utilization and fair allocation in both wireline and wireless networks, a common assumption therein is fixed link capacities. This unfortunately will limit the application scope in multi-hop wireless networks where channels are ever changing. In this paper, we explicitly model link capacities to be time varying and investigate congestion control problems in multi-hop wireless networks. In particular we propose a primal-dual congestion control algorithm which is proved to be trajectory stable in the absence of feedback delay. Different from system stability around a single equilibrium point, trajectory stability Guarantees the system is stable around a time varying reference trajectory. Moreover, we obtain sufficient conditions for the scheme to be locally stable in the presence of delay. Our key technique is to model time variations of capacities as perturbations to a constant link. Furthermore, to study the robustness of the algorithm against capacity variations, we investigate the sensitivity of the control scheme and through simulations to study the tradeoff between stability and sensitivity.
6564204
A robust method for shape-based 3D model retrieval
Proliferation of 3D models necessitates developing efficient methods for indexing or retrieving the models in a large database. Many previous methods for this purpose defined functions on concentric spheres as approximation of 3D geometry for spherical harmonic transform (SHT). In this paper, we point out that this is not robust as the surface of a model may shift between different shells under perturbation, and multi-layer of surfaces may exist in one shell, making the function definition ambiguous. To solve these problems, we propose a method to characterize 3D shape using delta functions. Then, spherical functions are defined by sampling in the frequency domain of the delta functions for SHT. By doing so, our method can support retrieval with controllable acuity, which benefits wider range of applications and facilitates customization to different users. Experiments have shown that our method is more robust than previous approaches.