The SKT reliability is the probability that a source can send communication to a specified set of terminals K in V in a probabilistic digraph D = (V, E). ''The most vital edge'' is the edge whose delet...
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The SKT reliability is the probability that a source can send communication to a specified set of terminals K in V in a probabilistic digraph D = (V, E). ''The most vital edge'' is the edge whose deletion yields the largest decrease in the SKT reliability. A digraph is a basically-series-parallel(BSP) directed graph if its underlying undirected graph is series-parallel. In this paper, we propose a tree-like structure and present an optimal algorithm with linear time complexity for finding the most vital edge with respect to SKT reliability in BSP digraphs.
A new algorithm is presented for finding a maximum independent set of a circular-arc graph. When the graph is given in the form of a family of n arcs, our algorithm requires only O(n⋅logn)<span style="display:...
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A non-blocking input buffered ATM switch that supports CBR and ABR traffic using a TDM scheduler frame is considered. A new TDM scheduler algorithm (largest-first) for CBR traffic is compared with four others, based o...
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A non-blocking input buffered ATM switch that supports CBR and ABR traffic using a TDM scheduler frame is considered. A new TDM scheduler algorithm (largest-first) for CBR traffic is compared with four others, based on the evenness of the distribution of unused timeslots in the scheduling frame. An even distribution of unused slots minimises the average latency and jitter for ABR traffic. Simulation results show that largest-first allocation is the best.
The O(h(4)) finite-difference scheme for the second derivative u ''(x) leads to a coherent pentadiagonal matrix which is factorized into two tridiagonal matrices. This factorization is used to derive an optima...
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The O(h(4)) finite-difference scheme for the second derivative u ''(x) leads to a coherent pentadiagonal matrix which is factorized into two tridiagonal matrices. This factorization is used to derive an optimal algorithm for solving a linear system of equations with the pentadiagonal matrix. As an application, a nonlinear system of ordinary differential equations is approximated by an O(h(4)) convergent finite-difference scheme. This scheme is solved by the implicit iterative method applying the algorithm at each iteration. A Mathematica module designed for the purpose of testing and using the method is attached.
A program is usually designed to act as a set of interacting tasks that can be used to construct a graph. These tasks can be assigned to processing elements in different ways. The scheduling problem is applied to defi...
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A program is usually designed to act as a set of interacting tasks that can be used to construct a graph. These tasks can be assigned to processing elements in different ways. The scheduling problem is applied to defining an assignment of tasks in order to process elements that will optimise certain performance indices. One of the most important reasons for scheduling indices is to try to optimise the finishing time. The finishing time of a program is the result of two components: the computing time and communication delays. An optimal schedule is defined as the one that assigns tasks to processing elements in such a way as to finish at the earliest possible time. Completion of the optimum solution for arbitrary directed acyclic task graphs (DAGs) has been shown to be NP-complete. However, for some special classes of DAGs (such as fork, join, coarse-grain trees and some fine grain trees) many algorithms have been introduced to find optimal schedules. Note that most of these algorithms do not take into consideration the delays due to message passing among the processors. In the paper, the authors study the increase in time complexity due to communication delays. The particular problem that is addressed is the scheduling problem of the in-forest/out-forest. This paper introduces the first known linear time algorithm for finding the optimal schedule, for the special case of tree-like graphs, with unit time computation and unit time communication delays.
This correspondence presents an optimal algorithm to detect any single "stuck-at-i," "stuck-at-O" fault and any combination of "stuck-at-I," "stuck-at-O" multiple faults in a ra...
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This correspondence presents an optimal algorithm to detect any single "stuck-at-i," "stuck-at-O" fault and any combination of "stuck-at-I," "stuck-at-O" multiple faults in a random access memory using only the n-bit memory address register input and m-bit memory buffer register input and output lines. It is shown that this algorithm requires 4 X 2n memory accesses.
Given n rectangles R-1, ..., R-n on the plane with sides parallel to the coordinate axes, Lipski and Preparata (1981) [1] have presented a Theta(n log n) time and O(n log n) space algorithm for computing the non-trivi...
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Given n rectangles R-1, ..., R-n on the plane with sides parallel to the coordinate axes, Lipski and Preparata (1981) [1] have presented a Theta(n log n) time and O(n log n) space algorithm for computing the non-trivial circuits of the union u = R-1 boolean OR ... boolean OR R-n. In this paper, we are presenting a simple algorithm, which computes the non-trivial circuits of u in Theta(n log n) time and Theta(n) space. (C) 2012 Elsevier B.V. All rights reserved.
This paper is a study on the problem of path planning for two robots on a grid. We consider the objective of minimizing the maximum path length which corresponds to minimizing the arrival time of the last robot at its...
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This paper is a study on the problem of path planning for two robots on a grid. We consider the objective of minimizing the maximum path length which corresponds to minimizing the arrival time of the last robot at its goal position. We propose an optimal algorithm that solves the problem in linear time with respect to the size of the grid. We show that the algorithm is complete;meaning that it is sure to find an optimal solution or report if any does not exist. (C) 2013 Elsevier B.V. All rights reserved.
Proper deployment of roadside units (RSUs) is of crucial importance to vehicular ad hoc networks (VANETs). However, our understandings to the simple one-dimensional RSU Deployment (D1RD) problem with nonuniform profit...
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Proper deployment of roadside units (RSUs) is of crucial importance to vehicular ad hoc networks (VANETs). However, our understandings to the simple one-dimensional RSU Deployment (D1RD) problem with nonuniform profit density is still seriously limited. In this paper, we analyze the D1RD problem and try to design optimal algorithms for it. We first analyze the properties of the optimal solutions of the D1RD problem involving a single RSU, and then extend to multiple RSUs. Next, we propose an efficient technique named Dynamic Limiting (DynLim), which reduces the solution search space size considerably by adjusting search space limits dynamically. Finally, an optimal algorithm named OptDynLim is proposed based on the DynLim technique, and its optimality is proved. Numerical simulations validate the correctness of our analyzes and show that DynLim can usually reduce solution search space size by more than 99%.
We consider the problem of separating a collection of isothetic polygons in the plane by translating one polygon at a time to infinity. The directions of translation are the four isothetic (parallel to the axes) direc...
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We consider the problem of separating a collection of isothetic polygons in the plane by translating one polygon at a time to infinity. The directions of translation are the four isothetic (parallel to the axes) directions, but a particular polygon can be translated only in one of these four directions. Our algorithm detects whether a scene is separable in this sense and computes a translational ordering of the polygons. The time and space complexities of our algorithm are O(n log n) and O(n) respectively, where n is the total number of vertices of the polygons in the scene. The best previous algorithm in the plane for this problem has complexities of O(n log(2) n) time and O(n log n) space. (C) 2003 Elsevier Inc. All rights reserved.
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