An Improved Link Model for Window Flow Control and Its Application to FAST TCP

This paper presents a link model which captures the queue dynamics in response to a change in a transmission control protocol (TCP) source's congestion window. By considering both self-clocking and the link integrator effect, the model generalizes existing models and is shown to be more accurate by both open loop and closed loop packet level simulations. It reduces to the known static link model when flows' round trip delays are identical, and approximates the standard integrator link model when there is significant cross traffic. We apply this model to the stability analysis of fast active queue management scalable TCP (FAST TCP) including its filter dynamics. Under this model, the FAST control law is linearly stable for a single bottleneck link with an arbitrary distribution of round trip delays. This result resolves the notable discrepancy between empirical observations and previous theoretical predictions. The analysis highlights the critical role of self-clocking in TCP stability, and the proof technique is new and less conservative than existing ones

Soldier/Hardware-in-the-loop Simulation-based Combat Vehicle Duty Cycle Measurement: Duty Cycle Experiment 2

This paper describes a human-in-the-loop motion-based simulator interfaced to hybrid-electric power system hardware both of which were used to measure the duty cycle of a combat vehicle in a virtual simulation environment. The project discussed is a greatly expanded follow-on to the experiment published in [1]. This paper is written in the context of [1] and therefore highlights the enhancements. The most prominent of these enhancements is the integration (in real-time) of the Power & Electric System Integration Lab (P&E SIL) with a motion base simulator by means of a “long haul” connection over the Internet (a geographical distance of 2,450 miles). The P&E SIL is, therefore, able to respond to commands issued by the vehicle’s driver and gunner and, in real-time, affect the simulated vehicle’s performance. By thus incorporating hardware into a human-in-the-loop experiment, TARDEC engineers are able to evaluate the actual power system as it responds to actual human behavior. After introducing the project, the paper describes the simulation environment which was assembled to run the experiment. It emphasizes the design of the experiment as well as the approach, challenges and issues involved in creating a real-time link between the motion-base simulator and the P&E SIL. It presents the test results and briefly discusses on-going and future work

Modeling and estimation techniques for understanding heterogeneous traffic behavior

The majority of current internet traffic is based on TCP. With the emergence of new applications, especially new multimedia applications, however, UDP-based traffic is expected to increase. Furthermore, multimedia applications have sparkled the development of protocols responding to congestion while behaving differently from TCP. As a result, network traffc is expected to become more and more diverse. The increasing link capacity further stimulates new applications utilizing higher bandwidths of future. Besides the traffic diversity, the network is also evolving around new technologies. These trends in the Internet motivate our research work. In this dissertation, modeling and estimation techniques of heterogeneous traffic at a router are presented. The idea of the presented techniques is that if the observed queue length and packet drop probability do not match the predictions from a model of responsive (TCP) traffic, then the error must come from non-responsive traffic; it can then be used for estimating the proportion of non-responsive traffic. The proposed scheme is based on the queue length history, packet drop history, expected TCP and queue dynamics. The effectiveness of the proposed techniques over a wide range of traffic scenarios is corroborated using NS-2 based simulations. Possible applications based on the estimation technique are discussed. The implementation of the estimation technique in the Linux kernel is presented in order to validate our estimation technique in a realistic network environment

The Impact of Speed Limits on Recreational Boating in the Lagoon of Venice

Speed limits were introduced in the Lagoon of Venice in 2002 to reduce wave motion, which damages environmentally sensitive areas in the broader Lagoon as well as buildings in the city of Venice. In this paper, we estimate the welfare losses experienced by recreational boaters as a result of the speed limits. We fit a single-site travel cost model to a sample of boaters intercepted as they depart from or arrive to marinas and launching ramps on the Lagoon. Our Poisson model is corrected for truncation and endogenous stratification. We construct three measures of the price per trip, which allow us to check the sensitivity of models and welfare estimates to possible measurement errors in the opportunity cost of time. Our results are robust to the measure of price used and conservatively peg the welfare losses of boaters to €7.7-9.6 million per year. Even under conservative assumptions, the welfare losses of boaters are sufficiently large that, given current monitoring and enforcement of the speed limits, we believe there is a strong incentive for boaters to disregard the limits.Travel cost method, Single-site model, Speed limits, Natural resources management

When Decision Meets Estimation: Theory and Applications

In many practical problems, both decision and estimation are involved. This dissertation intends to study the relationship between decision and estimation in these problems, so that more accurate inference methods can be developed. Hybrid estimation is an important formulation that deals with state estimation and model structure identification simultaneously. Multiple-model (MM) methods are the most widelyused tool for hybrid estimation. A novel approach to predict the Internet end-to-end delay using MM methods is proposed. Based on preliminary analysis of the collected end-to-end delay data, we propose an off-line model set design procedure using vector quantization (VQ) and short-term time series analysis so that MM methods can be applied to predict on-line measurement data. Experimental results show that the proposed MM predictor outperforms two widely used adaptive filters in terms of prediction accuracy and robustness. Although hybrid estimation can identify model structure, it mainly focuses on the estimation part. When decision and estimation are of (nearly) equal importance, a joint solution is preferred. By noticing the resemblance, a new Bayes risk is generalized from those of decision and estimation, respectively. Based on this generalized Bayes risk, a novel, integrated solution to decision and estimation is introduced. Our study tries to give a more systematic view on the joint decision and estimation (JDE) problem, which we believe the work in various fields, such as target tracking, communications, time series modeling, will benefit greatly from. We apply this integrated Bayes solution to joint target tracking and classification, a very important topic in target inference, with simplified measurement models. The results of this new approach are compared with two conventional strategies. At last, a surveillance testbed is being built for such purposes as algorithm development and performance evaluation. We try to use the testbed to bridge the gap between theory and practice. In the dissertation, an overview as well as the architecture of the testbed is given and one case study is presented. The testbed is capable to serve the tasks with decision and/or estimation aspects, and is helpful for the development of the JDE algorithms