Routers can use packet classification to support advanced functions. Routers with packet classification capability can forward packets based on multiple header fields, such as source address, protocol type, or applica...
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ISBN:
(纸本)0780370163
Routers can use packet classification to support advanced functions. Routers with packet classification capability can forward packets based on multiple header fields, such as source address, protocol type, or application port numbers. The destination-based forwarding can be thought of as one-dimensional packet classification. While several efficient solutions are known for the one-dimensional IP lookup problem, the multi-dimensional packet classification has proved to be far more difficult. While an O(log w) time scheme is known for the IP lookup, Srinivisan et al. (1999) show a lower bound of /spl Omega/(/spl omega//sup k-1/) for k-dimensional filter lookup, where /spl omega/ is the number of bits in a header field. In particular, this lower bound precludes the possibility of a binary search like scheme even for 2-dimensional filters. In this paper, we examine this lower bound more closely, and discover that the lower bound depends crucially on conflicts in the filter database. We then show that for two-dimensional conflict-free filters, a binary search scheme does work! Our lookup scheme requires O(log/sup 2/ /spl omega/) hashes in the worst-case, and uses O(n log/sup 2/ /spl omega/) memory. Alternatively, our algorithm can be viewed as making O (log /spl omega/) calls to a prefix lookup scheme. It has been observed in practice that filter databases have very few conflicts, and these conflicts can be removed by adding additional filters (one per conflict). Thus, our scheme may also be quite practical. Our simulation and experimental results show that the proposed scheme also performs as good as or better than existing schemes.
Our earlier work for fast evaluation of power consumption of general cores in a system-on-a-chip described techniques that involved isolating high-level instructions of a core, measuring gate-level power consumption p...
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ISBN:
(纸本)9780780366343
Our earlier work for fast evaluation of power consumption of general cores in a system-on-a-chip described techniques that involved isolating high-level instructions of a core, measuring gate-level power consumption per instruction, and then annotating a system-level simulation model with the obtained data. In this work, we describe a method for speeding up the evaluation further, through the use of instruction traces and trace simulators for every core, not just microprocessor cores. Our method shows noticeable speedups at an acceptable loss of accuracy. We show that reducing trace sizes can speed up the method even further. The speedups allow for more extensive system-level power exploration and hence better optimization.
The authors propose and demonstrate a novel all-optical return-to-zero (RZ) to non-return-to-zero (NRZ) data format conversion using a semiconductor optical amplifier (SOA) loop mirror. Error free transmission up to 7...
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ISBN:
(纸本)1557526559
The authors propose and demonstrate a novel all-optical return-to-zero (RZ) to non-return-to-zero (NRZ) data format conversion using a semiconductor optical amplifier (SOA) loop mirror. Error free transmission up to 78 km for the NRZ format converted data at 10 Gb/s is achieved. Also, the proposed method shows better transmission performance than the conventional Mach-Zehnder modulation method.
In this paper, we extend the Rao-Blackwellised particle filtering method to more complex hybrid models consisting of Gaussian latent variables and discrete observations. This is accomplished by augmenting the models w...
In this paper, we extend the Rao-Blackwellised particle filtering method to more complex hybrid models consisting of Gaussian latent variables and discrete observations. This is accomplished by augmenting the models with artificial variables that enable us to apply Rao-Blackwellisation. Other improvements include the design of an optimal importance proposal distribution and being able to swap the sampling an selection steps to handle outliers. We focus on sequential binary classifiers that consist of linear combinations of basis functions, whose coefficients evolve according to a Gaussian smoothness prior. Our results show significant improvements.
We report on a demonstration of x-ray-ultraviolet amplification following collisional excitation in a discharge-created plasma waveguide irradiated by a picosecond optical laser pulse. A capillary discharge was used t...
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We report on a demonstration of x-ray-ultraviolet amplification following collisional excitation in a discharge-created plasma waveguide irradiated by a picosecond optical laser pulse. A capillary discharge was used to generate a sulfur plasma column with a large concentration of Ne-like ions and a radially concave electron density profile. The intense short laser pulse rapidly heated the electrons, producing amplification in the 3p1S0–3s1P1 transition of Ne-like S at 60.8 nm. The integrated gain-length product obtained exciting a 3-cm-long capillary with a 0.46-J short laser pulse is 6.8. The beam divergence was observed to decrease as a function of plasma column length, reaching 2.5 mrad for 30-mm-long capillaries. This hybrid laser pumping scheme could lead to a new generation of efficient tabletop soft-x-ray lasers.
The purpose of this research is to determine an optimal batch size for a product, and the purchasing policy of associated raw materials, for a manufacturing firm. Like any other practical situation, this manufacturing...
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The purpose of this research is to determine an optimal batch size for a product, and the purchasing policy of associated raw materials, for a manufacturing firm. Like any other practical situation, this manufacturing firm has a limited storage space, and transportation fleet of known capacity. The mathematical formulation of the problem indicates that the model is a constrained nonlinear integer program. Considering the complexity of solving such a model, we investigate the use of genetic algorithms (GAs) for solving this model. We develop both binary and real coded genetic algorithms with six different penalty functions. In addition, we develop a new procedure to solve constrained optimization models using penalty function based GAs. The real coded genetic algorithms work well for the batch sizing problems. The detailed computational experiences are presented. International Federation of Operational Research Societies 2001.
We give the first construction of a pseudo-random generator with optimal seed length that uses (essentially) arbitrary hardness. It builds on the novel recursive use of the NW-generator in [8], which produced many opt...
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ISBN:
(纸本)9781581131840
We give the first construction of a pseudo-random generator with optimal seed length that uses (essentially) arbitrary hardness. It builds on the novel recursive use of the NW-generator in [8], which produced many optimal generators one of which was pseudo-random. This is achieved in two stages - first significantly reducing the number of candidate generators, and then efficiently combining them into one. We also give the first construction of an extractor with optimal seed length, that can handle sub-polynomial entropy levels. It builds on the fundamental connection between extractors and pseudo-random generators discovered by Trevisan, combined with construction above. Moreover, using Kolmogorov Complexity rather than circuit size in the analysis gives super-polynomial savings for our construction, and renders our extractors better than known for all entropy levels.
In this paper, we propose a full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that...
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ISBN:
(纸本)0262194503
In this paper, we propose a full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. We then propose a reversible jump Markov chain Monte Carlo (MCMC) method to perform the necessary computations. We find that the results are not only better than the previously reported ones, but also appear to be robust with respect to the prior specification. Moreover, we present a geometric convergence theorem for the algorithm.
The speech waveform can be modelled as a piecewise-stationary linear stochastic state space system, and its parameters can be estimated using an expectation-maximisation (EM) algorithm. One problem is the initialisati...
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ISBN:
(纸本)0262194503
The speech waveform can be modelled as a piecewise-stationary linear stochastic state space system, and its parameters can be estimated using an expectation-maximisation (EM) algorithm. One problem is the initialisation of the EM algorithm. Standard initialisation schemes can lead to poor formant trajectories. But these trajectories however are important for vowel intelligibility. The aim of this paper is to investigate the suitability of subspace identification methods to initialise EM. The paper compares the subspace state space system identification (4SID) method with the EM algorithm. The 4SID and EM methods are similar in that they both estimate a state sequence (but using Kalman filters and Kalman smoothers respectively), and then estimate parameters (but using least-squares and maximum likelihood respectively). The similarity of 4SID and EM motivates the use of 4SID to initialise EM. Also, 4SID is non-iterative and requires no initialisation, whereas EM is iterative and requires initialisation. However 4SID is sub-optimal compared to EM in a probabilistic sense. During experiments on real speech, 4SID methods compare favourably with conventional initialisation techniques. They produce smoother formant trajectories, have greater frequency resolution, and produce higher likelihoods.
In distributed real-time systems it is often useful for a process p to know that another process q will not use a certain piece of information that p has sent to q beyond a certain deadline. If p can learn about the o...
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In distributed real-time systems it is often useful for a process p to know that another process q will not use a certain piece of information that p has sent to q beyond a certain deadline. If p can learn about the occurrence of the deadline by simply measuring the passage of time on its own local clock, we call this kind of information exchange `communication by time'. It is shown that communication by time is possible in systems where there exists no a priori known upper bound on the transmission delay of messages and where clocks are not synchronized. It is sufficient if one can compute an a posteriori upper bound on the transmission delay of a message m, i.e. at the time when m is delivered. The authors show how one can compute an a posteriori upper bound on the one-way message transmission delay of a message even if the clocks of the sender and receiver process are not synchronized. The method is used to design a fail-aware datagram service. This service supports communication by time by delivering all messages whose computed one-way transmission delays are smaller than a given bound as `fast' and all other messages as `slow'. The properties of this service are specified and an efficient implementation is provided for it. To illustrate how this service supports communication by time, a leader election protocol that guarantees the existence of at most one leader at any real time is sketched and it is shown how this allows the detection of out-of-date sensor information in process control applications.
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