138 resultados para centralized algorithms

em Indian Institute of Science - Bangalore - Índia


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IEEE 802.16 standards for Wireless Metropolitan Area Networks (WMANs) include a mesh mode of operation for improving the coverage and throughput of the network. In this paper, we consider the problem of routing and centralized scheduling for such networks. We first fix the routing, which reduces the network to a tree. We then present a finite horizon dynamic programming framework. Using it we obtain various scheduling algorithms depending upon the cost function. Next we consider simpler suboptimal algorithms and compare their performances.

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Recently, efficient scheduling algorithms based on Lagrangian relaxation have been proposed for scheduling parallel machine systems and job shops. In this article, we develop real-world extensions to these scheduling methods. In the first part of the paper, we consider the problem of scheduling single operation jobs on parallel identical machines and extend the methodology to handle multiple classes of jobs, taking into account setup times and setup costs, The proposed methodology uses Lagrangian relaxation and simulated annealing in a hybrid framework, In the second part of the paper, we consider a Lagrangian relaxation based method for scheduling job shops and extend it to obtain a scheduling methodology for a real-world flexible manufacturing system with centralized material handling.

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The stimulation technique has gained much importance in the performance studies of Concurrency Control (CC) algorithms for distributed database systems. However, details regarding the simulation methodology and implementation are seldom mentioned in the literature. One objective of this paper is to elaborate the simulation methodology using SIMULA. Detailed studies have been carried out on a centralised CC algorithm and its modified version. The results compare well with a previously reported study on these algorithms. Here, additional results concerning the update intensiveness of transactions and the degree of conflict are obtained. The degree of conflict is quantitatively measured and it is seen to be a useful performance index. Regression analysis has been carried out on the results, and an optimisation study using the regression model has been performed to minimise the response time. Such a study may prove useful for the design of distributed database systems.

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A computational study for the convergence acceleration of Euler and Navier-Stokes computations with upwind schemes has been conducted in a unified framework. It involves the flux-vector splitting algorithms due to Steger-Warming and Van Leer, the flux-difference splitting algorithms due to Roe and Osher and the hybrid algorithms, AUSM (Advection Upstream Splitting Method) and HUS (Hybrid Upwind Splitting). Implicit time integration with line Gauss-Seidel relaxation and multigrid are among the procedures which have been systematically investigated on an individual as well as cumulative basis. The upwind schemes have been tested in various implicit-explicit operator combinations such that the optimal among them can be determined based on extensive computations for two-dimensional flows in subsonic, transonic, supersonic and hypersonic flow regimes. In this study, the performance of these implicit time-integration procedures has been systematically compared with those corresponding to a multigrid accelerated explicit Runge-Kutta method. It has been demonstrated that a multigrid method employed in conjunction with an implicit time-integration scheme yields distinctly superior convergence as compared to those associated with either of the acceleration procedures provided that effective smoothers, which have been identified in this investigation, are prescribed in the implicit operator.

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Doppler weather radars with fast scanning rates must estimate spectral moments based on a small number of echo samples. This paper concerns the estimation of mean Doppler velocity in a coherent radar using a short complex time series. Specific results are presented based on 16 samples. A wide range of signal-to-noise ratios are considered, and attention is given to ease of implementation. It is shown that FFT estimators fare poorly in low SNR and/or high spectrum-width situations. Several variants of a vector pulse-pair processor are postulated and an algorithm is developed for the resolution of phase angle ambiguity. This processor is found to be better than conventional processors at very low SNR values. A feasible approximation to the maximum entropy estimator is derived as well as a technique utilizing the maximization of the periodogram. It is found that a vector pulse-pair processor operating with four lags for clear air observation and a single lag (pulse-pair mode) for storm observation may be a good way to estimate Doppler velocities over the entire gamut of weather phenomena.

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We propose four variants of recently proposed multi-timescale algorithm in [1] for ant colony optimization and study their application on a multi-stage shortest path problem. We study the performance of the various algorithms in this framework. We observe, that one of the variants consistently outperforms the algorithm [1].

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Two algorithms that improve upon the sequent-peak procedure for reservoir capacity calculation are presented. The first incorporates storage-dependent losses (like evaporation losses) exactly as the standard linear programming formulation does. The second extends the first so as to enable designing with less than maximum reliability even when allowable shortfall in any failure year is also specified. Together, the algorithms provide a more accurate, flexible and yet fast method of calculating the storage capacity requirement in preliminary screening and optimization models.

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The paper presents two new algorithms for the direct parallel solution of systems of linear equations. The algorithms employ a novel recursive doubling technique to obtain solutions to an nth-order system in n steps with no more than 2n(n −1) processors. Comparing their performance with the Gaussian elimination algorithm (GE), we show that they are almost 100% faster than the latter. This speedup is achieved by dispensing with all the computation involved in the back-substitution phase of GE. It is also shown that the new algorithms exhibit error characteristics which are superior to GE. An n(n + 1) systolic array structure is proposed for the implementation of the new algorithms. We show that complete solutions can be obtained, through these single-phase solution methods, in 5n−log2n−4 computational steps, without the need for intermediate I/O operations.

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Based on trial interchanges, this paper develops three algorithms for the solution of the placement problem of logic modules in a circuit. A significant decrease in the computation time of such placement algorithms can be achieved by restricting the trial interchanges to only a subset of all the modules in a circuit. The three algorithms are simulated on a DEC 1090 system in Pascal and the performance of these algorithms in terms of total wirelength and computation time is compared with the results obtained by Steinberg, for the 34-module backboard wiring problem. Performance analysis of the first two algorithms reveals that algorithms based on pairwise trial interchanges (2 interchanges) achieve a desired placement faster than the algorithms based on trial N interchanges. The first two algorithms do not perform better than Steinberg's algorithm1, whereas the third algorithm based on trial pairwise interchange among unconnected pairs of modules (UPM) and connected pairs of modules (CPM) performs better than Steinberg's algorithm, both in terms of total wirelength (TWL) and computation time.

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In this paper, the design and implementation of a single shared bus, shared memory multiprocessing system using Intel's single board computers is presented. The hardware configuration and the operating system developed to execute the parallel algorithms are discussed. The performance evaluation studies carried out on Image are outlined.

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The Reeb graph tracks topology changes in level sets of a scalar function and finds applications in scientific visualization and geometric modeling. We describe an algorithm that constructs the Reeb graph of a Morse function defined on a 3-manifold. Our algorithm maintains connected components of the two dimensional levels sets as a dynamic graph and constructs the Reeb graph in O(nlogn+nlogg(loglogg)3) time, where n is the number of triangles in the tetrahedral mesh representing the 3-manifold and g is the maximum genus over all level sets of the function. We extend this algorithm to construct Reeb graphs of d-manifolds in O(nlogn(loglogn)3) time, where n is the number of triangles in the simplicial complex that represents the d-manifold. Our result is a significant improvement over the previously known O(n2) algorithm. Finally, we present experimental results of our implementation and demonstrate that our algorithm for 3-manifolds performs efficiently in practice.

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This letter presents the development of simplified algorithms based on Haar functions for signal extraction in relaying signals. These algorithms, being computationally simple, are better suited for microprocessor-based power system protection relaying. They provide accurate estimates of the signal amplitude and phase.

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A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

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In this paper, three parallel polygon scan conversion algorithms have been proposed, and their performance when executed on a shared bus architecture has been compared. It has been shown that the parallel algorithm that does not use edge coherence performs better than those that use edge coherence. Further, a multiprocessing architecture has been proposed to execute the parallel polygon scan conversion algorithms more efficiently than a single shared bus architecture.

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The implementation of CSP-S (a subset of CSP)—a high level language for distributed programming—is presented in this paper. The language CSP-S features a parallel command, communication by message passing and the use of guarded command. The implementation consists of a compiler translating the CSP-S constructs into intermediate language. The execution is carried out by a scheduler which creates an illusion of concurrency. Using the CSP-S language constructs, distributed algorithms are written, executed and tested with the compiler designed.