This paper gives a class of flow control algorithms for the adaptive allocation of bandwidths to virtual connections (VC) in high-speed, wide-area ATM networks, The feedback rate to the source from the network is pars...
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This paper gives a class of flow control algorithms for the adaptive allocation of bandwidths to virtual connections (VC) in high-speed, wide-area ATM networks, The feedback rate to the source from the network is parsimonious, with each feedback bit indicating whether the buffer at a distant switch is above or below a threshold. The service discipline at the switch is First-Come-First-Served. The important goal of adaptability aims to make all of the network bandwidth available to the active VC's, even though the number of such VC's is variable over a given range. Each VC has two parameters, one giving its minimum guaranteed bandwidth and the other is the weight for determining its share of the uncommitted bandwidth. Judicious selection of these parameters defines distinctive services, such as Best Effort and Best Effort with Minimum Bandwidth, We derive design rules for selecting the parameters of the algorithms such that the appropriate guarantees and fairness properties are exhibited in the dynamical behavior, The systematic use of ''damping'' in right proportion with ''gain'' is shown to be a powerful device for stabilizing behavior and achieving fairness, Our analyses are based on a simple analytic fluid model composed of a system of first-order delay-differential equations, which reflect the propagation delay across the network. Extensive simulations examine the following: (1) fairness, especially to start-up VC's;(2) oscillations;(3) transient behavior, such as the rate of equalization from different initial conditions;(4) disparate bandwidth allocations;(5) multiple paths with diverse propagation delays;(5) adaptability and robustness with respect to parameters;and (7) interoperability of different algorithms.
The PARAFAC decomposition of a higher-order tensor is a powerful multilinear algebra tool that becomes more and more popular in a number of disciplines. Existing PARAFAC algorithms are computationally demanding and op...
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The PARAFAC decomposition of a higher-order tensor is a powerful multilinear algebra tool that becomes more and more popular in a number of disciplines. Existing PARAFAC algorithms are computationally demanding and operate in batch mode-both serious drawbacks for on-line applications. When the data are serially acquired, or the underlying model changes with time, adaptive PARAFAC algorithms that can track the sought decomposition at low complexity would be highly desirable. This is a challenging task that has not been addressed in the literature, and the topic of this paper. Given an estimate of the PARAFAC decomposition of a tensor at instant t, we propose two adaptive algorithms to update the decomposition at instant t + 1, the new tensor being obtained from the old one after appending a new slice in the 'time' dimension. The proposed algorithms can yield estimation performance that is very close to that obtained Via repeated application of state-of-art batch algorithms, at orders of magnitude lower complexity. The effectiveness of the proposed algorithms is illustrated using a MIMO radar application (tracking of directions of arrival and directions of departure) as an example.
Distributed query processing algorithms usually perform data reduction by using a semijoin program, but the problem with these approaches is that they still require an explicit join of the reduced relations in the fin...
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Distributed query processing algorithms usually perform data reduction by using a semijoin program, but the problem with these approaches is that they still require an explicit join of the reduced relations in the final phase. We introduce an efficient algorithm for join processing in distributed database systems that makes use of bipartite graphs in order to reduce data communication costs and local processing costs. The bipartite graphs represent the tuples that can be joined in two relations taking also into account the reduction state of the relations. This algorithm fully reduces the relations at each site. We then present an adaptive algorithm for response time optimization that takes into account the system configuration, i.e., the additional resources available and the data characteristics, in order to select the best strategy for response time minimization. We also report on the results of a set of experiments which show that our algorithms outperform a number of the recently proposed methods for total processing time and response time minimization.
Since direct numerical solution of a non-convex variational problem (P) yields rapid oscillations, we study the relaxed problem (RP) which is a degenerate convex minimization problem. The classical example for such a ...
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Since direct numerical solution of a non-convex variational problem (P) yields rapid oscillations, we study the relaxed problem (RP) which is a degenerate convex minimization problem. The classical example for such a relaxed variational problem is the double-well problem. In an earlier work, the authors showed that relaxation is not linked to a loss of information if our main interest concerns the macroscopic displacement field, the stress field or the microstructure. Furthermore, a priori and a posteriori error estimates have been computed and an adaptive algorithm was proposed for this class of degenerate variational problems. This paper addresses the question of efficiency and considers the ZZ-indicator, named after Zienkiewicz and Zhu, and discusses its performance compared with the rigorous indicator introduced by the authors. (C) 1998 Elsevier Science B.V.
We study problems in computational geometry from the viewpoint of adaptive algorithms. adaptive algorithms have been extensively studied for the sorting problem, and in this paper we generalize the framework to geomet...
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We study problems in computational geometry from the viewpoint of adaptive algorithms. adaptive algorithms have been extensively studied for the sorting problem, and in this paper we generalize the framework to geometric problems. To this end, we think of geometric problems as permutation (or rearrangement) problems of arrays, and define the "presortedness" as a distance from the input array to the desired output array. We call an algorithm adaptive if it runs faster when a given input array is closer to the desired output, and furthermore it does not make use of any information of the presortedness. As a case study, we look into the planar convex hull problem for which we discover two natural formulations as permutation problems. An interesting phenomenon that we prove is that for one formulation the problem can be solved adaptively, but for the other formulation no adaptive algorithm can be better than an optimal output-sensitive algorithm for the planar convex hull problem. To further pursue the possibility of adaptive computational geometry, we also consider constructing a kd-tree.
Two algorithms are presented for the rejection of sinusoidal disturbances with unknown frequency. The first is an indirect algorithm where the Frequency of the disturbance is estimated, and the estimate is used in ano...
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Two algorithms are presented for the rejection of sinusoidal disturbances with unknown frequency. The first is an indirect algorithm where the Frequency of the disturbance is estimated, and the estimate is used in another adaptive algorithm that adjusts the magnitude and phase of the input needed to cancel the effect of the disturbance. A direct algorithm that uses the concept of a phase-locked loop is also presented in which frequency estimation and disturbance cancellation are performed simultaneously. Approximate analyses are presented for both schemes and the results are found useful for the selection of the design parameters. Simulations are given which demonstrate the validity of the analytical results and the ability of the algorithms to reject sinusoidal disturbances with unknown frequency. The indirect algorithm is found to have a larger capture region for the parameter estimates, whereas the direct algorithm has superior convergence properties locally about the optimum parameter estimates. (C) 1997 Elsevier Science Ltd. All rights reserved.
Upcoming sensor networks would be deployed with sensing devices with energy harvesting capabilities from renewable energy sources such as solar power. A key research question in such sensor systems is to maximize the ...
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Upcoming sensor networks would be deployed with sensing devices with energy harvesting capabilities from renewable energy sources such as solar power. A key research question in such sensor systems is to maximize the asymptotic event detection probability achieved in the system, in the presence of energy constraints and uncertainties. This paper focuses on the design of adaptive algorithms for sensor activation in the presence of uncertainty in the event phenomena. Based upon the ideas from increase/decrease algorithms used in TCP congestion avoidance, we design an online and adaptive activation algorithm that varies the subsequent sleep interval according to additive increase and multiplicative decrease depending upon the sensor's current energy level. In addition, the proposed algorithm does not depend on global system parameters, or on the degree of event correlations, and hence can easily be deployed in practical scenarios. We analyze the performance of proposed algorithm for a single sensor scenario using Markov chains, and show that the proposed algorithm achieves near-optimal performance. Through extensive simulations, we demonstrate that the proposed algorithm not only achieves near-optimal performance, but also exhibits more stability with respect to sensor's energy level and sleep interval variations. We validate the applicability of our proposed algorithm in the presence of multiple sensors and multiple event processes through simulations. (c) 2011 Elsevier B.V. All rights reserved.
The boundary value problem (BVP) for a scalar nonlinear second order differential equation on the half-axis is considered. A constructive method is proposed to derive from the three-point exact difference scheme (EDS)...
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The boundary value problem (BVP) for a scalar nonlinear second order differential equation on the half-axis is considered. A constructive method is proposed to derive from the three-point exact difference scheme (EDS) a so-called truncated difference scheme (n-TDS) of rank it, where it is a freely chosen natural number. The n-TDS has the order of accuracy (n) over bar = 2 vertical bar(n + 1)/2 vertical bar, i.e., the global error is of the form O(vertical bar h vertical bar((n) over bar)), where vertical bar h vertical bar is the maximum step size and vertical *** bar denotes the entire part of the expression in brackets. This n-TDS is the basis for a new adaptive algorithm which has all the advantages known from the modern IVP-solvers. Numerical examples are given which confirm the efficiency and reliability of our algorithm. (C) 2008 IMACS. Published by Elsevier B.V. All rights reserved.
In this paper, we investigate adaptive algorithms for solving generalized eigenvalue problems that arise in the context of signal enhancement. This problem applies in general to any setup involving vectors of signal a...
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In this paper, we investigate adaptive algorithms for solving generalized eigenvalue problems that arise in the context of signal enhancement. This problem applies in general to any setup involving vectors of signal and interference samples, including wideband temporal processing, diffuse spatial (array) processing, or any combination thereof The algorithms attempt to solve a generalized eigenvalue (GEV) problem using only snapshots of signal and interference training vectors, and the goal is to do this with a minimum amount of data and computational resources. The algorithms considered fall into two classes: two-step approaches that first estimate the covariance matrices and then solve the GEV problem;and, stochastic gradient type algorithms that recursively update the solution in one step for each new set of data vector snapshots. The algorithms are compared on the basis of convergence rate and computational complexity. (C) 2003 Elsevier B.V. All rights reserved.
In this paper sound steganographic system receiver structure with signal spectrum broadening is proposed and researched. This receiver consists of rehabilitate filter with adaptive coefficients and correlation receive...
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