TCP Westwood (TCPW) is a sender-side modification of the TCP congestion window algorithm that improves upon the performance of TCP Reno in wired as well as wireless networks. The improvement is most significant in wireless networks with lossy links, since TCP Westwood relies on endto-end bandwidth estimation to discriminate the cause of packet loss (congestion or wireless channel effect) which is a major problem in TCP Reno. An important distinguishing feature of TCP Westwood with respect to previous wireless TCP “extensions ” is that it does not require inspection and/or interception of TCP packets at intermediate (proxy) nodes. Rather, it fully complies with the end-to-end TCP design principle. The key innovative idea is to continuously measure at the TCP source the rate of the connection by monitoring the

A development of a method for tracking visual contours is described. Given an "un-trained" tracker, a training-motion of an object can be observed over some extended time and stored as an image sequence. The image sequence is used to learn parameters in a stochastic differential equation model. These are used, in turn, to build a tracker whose predictor imitates the motion in the training set. Tests show that the resulting trackers can be markedly tuned to desired curve shapes and classes of motions. Contents 1 Introduction 2 2 Tracking framework 2 2.1 Curve representation : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 2 2.2 Tracking as estimation over time : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 2.3 Rigid body transformations : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 2.4 Curves in motion : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 7 2.5 Discrete-time model : : : : : : : : : :...

AbstractÐStandard, exact techniques based on likelihood maximization are available for learning Auto-Regressive Process models of dynamical processes. The uncertainty of observations obtained from real sensors means that dynamics can be observed only approximately. Learning can still be achieved via ªEM-KºÐExpectation-Maximization (EM) based on Kalman Filtering. This cannot handle more complex dynamics, however, involving multiple classes of motion. A problem arises also in the case of dynamical processes observed visually: background clutter arising for example, in camouflage, produces non-Gaussian observation noise. Even with a single dynamical class, non-Gaussian observations put the learning problem beyond the scope of EM-K. For those cases, we show here how ªEM-CºÐbased on the CONDENSATION algorithm which propagates random ªparticle-sets,º can solve the learning problem. Here, learning in clutter is studied experimentally using visual observations of a hand moving over a desktop. The resulting learned dynamical model is shown to have considerable predictive value: When used as a prior for estimation of motion, the burden of computation in visual observation is significantly reduced. Multiclass dynamics are studied via visually observed juggling; plausible dynamical models have been found to emerge from the learning process, and accurate classification of motion has resulted. In practice, EM-C learning is computationally burdensome and the paper concludes with some discussion of computational complexity. Index TermsÐComputer vision, learning dynamics, Auto-Regressive Process, Expectation Maximization. 1

This paper presents a feedback control algorithm for ATM congestion control in which source rates are adjusted according to VC queue lengths at intermediate nodes along the path. The goal is to "fill in" the residual bandwidth, without exceeding a specified queue threshold. In order to obtain this, we propose a simple and classical proportional controller, plus a Smith Predictor to overcome instabilities due to large propagation delays, as well as to avoid cell loss. We propose an effective EPRCA implementation in which each source computes its input rate based on the maximum VC queue length along the path. Theoretical and experimental results show that high throughput is achieved even with queue sizes independent of the round trip delay. 1 Introduction In an ATM network, in order to avoid congestion it is necessary to regulate the input traffic rate of the network such that all entering cells can be completely delivered using the existing network resources (i.e. queues, processing p...

TCP Westwood (TCPW) is a sender-side modification of the TCP congestion window algorithm that improves upon the performance of TCP Reno in wired as well as wireless networks. The improvement is most significant in wireless networks with lossy links. In fact, TCPW performance is not very sensitive to random errors, while TCP Reno is equally sensitivity to random loss and congestion loss and cannot discriminate between them. Hence, the tendency of TCP Reno to overreact to errors. An important distinguishing feature of TCP Westwood with respect to previous wireless TCP "extensions" is that it does not require inspection and/or interception of TCP packets at intermediate (proxy) nodes. Rather, TCPW fully complies with the end-to-end TCP design principle. The key innovative idea is to continuously measure at the TCP sender side the bandwidth used by the connection via monitoring the rate of returning ACKs. The estimate is then used to compute congestion window and slow start threshold after a congestion episode, that is, after three duplicate acknowledgments or after a timeout. The rationale of this strategy is simple: in contrast with TCP Reno which "blindly" halves the congestion window after three duplicate ACKs, TCP Westwood attempts to select a slow start threshold and a congestion window which are consistent with the effective bandwidth used at the time congestion is experienced. We call this mechanism faster recovery. The proposed mechanism is particularly effective over wireless links where sporadic losses due to radio channel problems are often misinterpreted as a symptom of congestion by current TCP schemes and thus lead to an unnecessary window reduction. Experimental studies reveal improvements in throughput performance, as well as in fairness. In addition, fri...

We present a method of translating discrete-time Simulink models to Lustre programs. Our method consists of three steps: type inference, clock inference and hierarchical bottom-up translation. In the process, we formalize typing and timing mechanisms of Simulink. The method has been implemented in a prototype tool called S2L. The tool has been used to translate part of an industrial automotive controller provided by Audi. 1

In this paper, we propose an extension of TCP Westwood allowing the management of the Efficiency/Friendliness-toNewReno tradeoffs. We show that the extended TCP Westwood is able to achieve higher total link utilization, yet at the same time maintain friendliness. TCP Westwood (for short, TCPW) implements a novel window congestion control algorithm based on eligible rate estimation. The performance of TCPW has been promising, exceeding that of TCP NewReno in "large leaky pipes"; i.e. network paths with high bandwidth-delay product and non-negligible random error rate. Consider the situation where TCPW and TCP NewReno connections coexist and share common bottlenecks. Friendliness in this shared environment is paramount. Under certain conditions TCP NewReno may experience some performance degradation since TCPW "learns" more about connection performance and thus can take better advantage of available bandwidth. To manage the efficiency/friendliness tradeoffs, we propose to combine the original TCPW Bandwidth Estimation (BE) strategy with a new Rate Estimation (RE) strategy. One finds that BE provides significantly higher utilization, but may, under certain conditions, overestimates a connection fair share. RE, on the other hand, tends to be closer to the achieved rate of a connection, but it may underestimate the connection fair share. The question is: which estimate -- RE or BE -- yields better throughput/friendliness tradeoffs? Our studies show that RE works best when packet loss is mostly due to congestion. If, on the other hand, packet loss is mostly due to link errors, BE gives better performance. To achieve the "best of all worlds", we introduce a method we call Combined Rate and Bandwidth estimation (CRB.) A connection first infers the predominant cause of packet lo...

Abstract — Digital implementations of feedback laws commonly consider periodic execution of control tasks. In this paper we go beyond the periodic model by developing self-triggered schedules for the execution of control tasks. These schedules guarantee asymptotic stability under sample-and-hold implementations while drastically reducing processor usage when compared with the more traditional periodic implementations. At the technical level the results rely on a homogeneity assumption on the continuous dynamics and extend to the selftriggered framework some of the advantages of event-triggered implementations recently studied by the authors. The results presented in this paper can be seen as an effort towards understanding the real-time scheduling requirements of control tasks. I.

We present a method of translating discrete-time Simulink models to Lustre programs. Our method consists of three steps: type inference, clock inference and hierarchical bottom-up translation. In the process, we explain and formalize the typing and timing mechanisms of Simulink. The method has been implemented in a prototype tool called S2L. The tool has been used in the context of a European research project to translate two automotive controller models provided by Audi.

Today TCP/IP congestion control implements the additive increase/multiplicative decrease (AIMD) paradigm to probe network capacity and obtain a "rough" but robust measurement of the best effort available bandwidth. Westwood TCP proposes an additive increase/adaptive decrease paradigm that adaptively sets the transmission rate at the end of the probing phase to match the bandwidth used at the time of congestion, which is the definition of best-effort available bandwidth in a connectionless packet network. This paper addresses the challenging issue of estimating the best effort bandwidth available for a TCP/IP connection by properly counting and filtering the flow of acknowledgments packets using discrete-time filters. We show that in order to implement a low-pass filter in packet networks it is necessary to implement an anti ACK compression algorithm, which plays the role of a classic anti-aliasing filter. Moreover, a comparison of time-invariant and time-varying discrete filters to be used after the anti-aliasing algorithm is developed.