16022661
Monitoring access link capacity using TFRC probe
Accurate estimation of network characteristics based on end-to-end measurements is an important and challenging problem. With the increasing variety and sophistication of Internet access methods, the mobility of the users and the need for seamless handoff across them, monitoring access link capacity becomes critical for efficient multimedia delivery. In fact, this allows the multimedia server to properly adjust its sending rate to the rapidly changing access speed of the mobile client. This problem is challenging because most of the existing capacity monitoring schemes are active, like Pathrate (and therefore, introduce extra overhead on the bandwidth limited access link). Moreover, the access link is often asymmetric (e.g. ADSL, 1xRTT, etc.) thus preventing the use of round-trip monitoring schemes such as Pathchar and CapProbe. In this study, we propose and evaluate a passive, one-way link capacity monitoring tool called TFRC Probe. With TFRC Probe the source can monitor the forward direction capacity of both asymmetric and symmetric access links, and can rapidly and accurately adapt its transmissions rate accordingly. We validate TFRC Probe with both simulation and testbed experiments, and show that TFRC Probe is a very flexible tool that can accurately track frequent changes in access capacity.
18494182
Improving Bluetooth EDR Data Throughput Using FEC and Interleaving
Wireless communication is inherently vulnerable to errors from the dynamic wireless environment. Link layer packets discarded due to these errors impose a serious limitation on the maximum achievable throughput in the wireless channel. To enhance the overall throughput of wireless communication, it is necessary to deploy link layer transmission schemes that is robust to the errors intrinsic to the wireless channel. In this paper, we investigated the impact of three link layer enhancement techniques on the new Enhanced Data Rate (EDR) mode detailed in the new Bluetooth spec v2.0. We first studied the APT algorithm, and used it to obtain the optimal packet type for different bit error rates. We then evaluated FEC/IFEC coding schemes for the new EDR packet types, assessed their ability to alleviate the impact of burst errors, and discussed the tradeoffs. Using analysis and simulation, we show that the performance of the new Bluetooth EDR mode can be significantly improved when FEC and/or IFEC techniques are employed.
62256007
CapProbe: a simple and accurate capacity estimation technique
We present a new capacity estimation technique, called CapProbe. CapProbe combines delay as well as dispersion measurements of packet pairs to filter out samples distorted by cross-traffic. CapProbe algorithms include convergence tests and convergence speed-up techniques by varying probing parameters. Our study of CapProbe includes a probability analysis to determine the time it takes CapProbe to converge on the average. Through simulations and measurements, we found CapProbe to be quick and accurate across a wide range of traffic scenarios. We also compared CapProbe with two previous well-known techniques, pathchar and pathrate. We found CapProbe to be much more accurate than pathchar and similar in accuracy to pathrate, while providing faster estimation than both. Another advantage of CapProbe is its lower computation cost, since no statistical post processing of probing data is required.
1912999
Improving wireless link throughput via interleaved FEC
Wireless communication is inherently vulnerable to errors from the dynamic wireless environment. Link layer packets discarded due to these errors impose a serious limitation on the maximum achievable throughput in the wireless channel. To enhance the overall throughput of wireless communication, it is necessary to have a link layer transmission scheme that is robust to the errors intrinsic to the wireless channel. To this end, we present interleaved-forward error correction (I-FEC), a clever link layer coding scheme that protects link layer data against random and busty errors. We examine the level of data protection provided by I-FEC against other popular schemes. We also simulate I-FEC in Bluetooth, and compare the TCP throughput result with Bluetooth's integrated FEC coding feature. We show that I-FEC consistently and significantly outperforms other link layer coding schemes by providing an impressive amount of protection against heavy channel burst errors.
10161187
Accuracy of link capacity estimates using passive and active approaches with CapProbe
CapProbe is an inexpensive and accurate means to estimate capacity. CapProbe combines both dispersion and end-to-end delay to estimate the capacity of the narrowest link on a path. We evaluate in this paper the accuracy of CapProbe estimation, and its dependence on end systems speed, packet sizes, narrow link speeds, and other system parameters. We test kernel and user level implementations of CapProbe and find the kernel implementation to be much more accurate. We also evaluate through experiments the effect of probing packet size on the accuracy of CapProbe estimation. Finally, we explore the idea of a "passive CapProbe" within the context of a TCP flow. Passive here means that the dispersion and delay observed for the TCP flow data and ACK packets, without introducing any additional probing packets. We test active and passive versions of CapProbe with TCP. The active version is found to produce more accurate capacity estimates than the passive version.
8697404
Audio streaming over Bluetooth: an adaptive ARQ timeout approach
Streaming audio has become a popular form of media on the Internet. As wireless personal area network architectures (e.g. Bluetooth) are now targeted to support multimedia traffic, streaming audio over these technologies give rise to interesting applications. But, the variable nature of the wireless medium will not lend itself easily to supporting audio streaming. We focus on Bluetooth and propose, an enhancement to the Bluetooth link layer ARQ mechanism to compensate for channel degradation and to better support audio streaming. Specifically, our scheme adoptively sets the ARQ timeout value based on current channel measurements. We show through testbed experiments that the adaptive ARQ improves the streaming quality significantly compared to the "vanilla" link layer of Bluetooth, especially in noisy environments. Our proposed approach is simple to implement and can actually be extended to the link layer of any wireless technology.
5417653
On the Web Data Extraction Model
43431226
Wavelet-based optical flow estimation
A new algorithm for accurate optical flow (OF) estimation using discrete wavelet approximation is proposed. The computation of OF depends on minimizing the image and smoothness constraints. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately approximate any function. OF vectors and image functions are represented by means of linear combinations of scaling basis functions. Based on such wavelet-based approximation, the leading coefficients of these basis functions carry global information about the approximated functions. The proposed method can successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of scaling coefficients. Once all the corresponding coefficients are determined, the flow vectors can be obtained accordingly. Experiments have been conducted on both synthetic and real image sequences. In terms of accuracy, the results show that our approach outperforms the existing methods which adopted the same objective function as ours.
31293594
Integrating mRNA Decay Information into Co-Regulation Study
Absolute or relative transcript amounts measured through high-throughput technologies (e.g., microarrays) are now commonly used in bioinformatics analysis, such as gene clustering and DNA binding motif finding. However, transcription rates that represent mRNA synthesis may be more relevant in these analyses. Because transcription rates are not equivalent to transcript amounts unless the mRNA degradation rates as well as other factors that affect transcript amount are identical across different genes, the use of transcription rates in bioinformatics analysis may lead to a better description of the relationships among genes and better identification of genomic signals. In this article, we propose to use experimentally measured mRNA decay rates and mRNA transcript amounts to jointly infer transcription rates, and then use the inferred transcription rates in downstream analyses. For gene expression similarity analysis, we find that there tends to be higher correlations among co-regulated genes when transcription-rate-based correlations are used compared to those based on transcript amounts. In the context of identifying DNA binding motifs, using inferred transcription rates leads to more significant findings than those based on transcript amounts. These analyses suggest that the incorporation of mRNA decay rates and the use of the inferred transcription rates can facilitate the study of gene regulations and the reconstruction of transcriptional regulatory networks.
2039675
On Detection of Bounded Global Predicates
Distributed programs often follow some bounded global predicates, for example, the total number of certain tokens is always the same or bounded in a range. In order to detect bounded global predicates, we can first derive the minimum and maximum global snapshots and then check if the minimum and maximum are out of the range. Recently, Chase and Garg proposed an efficient method to derive the minimum global snapshot by reducing this problem to a maximum network flow problem. A restriction of this method is that all message values (e.g., the token number in messages) must be zero and all process state values (e.g., the token number in processes) must be non-negative. In this paper, we propose an elegant technique, called normalization. By using this technique, we can remove the above restriction and also derive the minimum and maximum global snapshots at the same time.
7815226
Peak Load Forecasting Using the Self-organizing Map
This paper aims to study the short-term load forecasting of electricity by using an extended self-organizing map. We first adopt a traditional Kohonen self-organizing map (SOM) to learn time-series load data with weather information as parameters. Then, in order to improve the accuracy of the prediction, an extension of SOM algorithm based on error-correction learning rule is used, and the estimation of the peak load is achieved by averaging the output of all the neurons. Finally, as an implementation example, data of electricity demand from New York Independent System Operator (ISO) are used to verify the effectiveness of the learning and prediction for the proposed methods.