In this paper, based on the Position Maintaining Strategy (PMS for short), on-line scheduling of k-truck problem, which is a generalization of the famous k-server problem, is originally presented by our team. We propo...
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In this paper, based on the Position Maintaining Strategy (PMS for short), on-line scheduling of k-truck problem, which is a generalization of the famous k-server problem, is originally presented by our team. We proposed several competitive algorithms applicable under different conditions for solving the on-line k-truck problem. First, a competitive algorithm with competitive ratio 2k + 1/theta is given for any theta greater than or equal to 1. Following that, if theta greater than or equal to (c + 1)/(c - 1) holds, then there must exist a (2k - 1)-competitive algorithm for k-truck problem, where c is the competitive ratio of the on-line algorithm about the relevant k-server problem. And then a greedy algorithm with competitive ratio 1 + lambda/theta, where lambda is a parameter related to the structure property of a given graph, is given. Finally, competitive algorithms with ratios 1 + 1/theta are given for two special families of graphs.
We consider the following motion planning problem for a point robot inside a simple polygon P: starting from an arbitrary point s of P, the robot aims at reaching the closest point t of P from where the entire polygon...
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ISBN:
(纸本)3540676902
We consider the following motion planning problem for a point robot inside a simple polygon P: starting from an arbitrary point s of P, the robot aims at reaching the closest point t of P from where the entire polygon P can be seen;the robot does not have complete knowledge of P but is equipped with a 360-degree vision system that helps it "see" its surrounding space. We are interested in a competitive path planning algorithm, i.e., one that produces a path whose length does not exceed a constant c times the length of the shortest off-line path tin this case, c x distance(s, t));the constant c is called the competitive factor. In this paper, we present a new strategy that achieves a competitive factor of similar to3.126, improving over a 4.14-competitive strategy of Icking and Klein and a 3.829-competitive strategy of Lee et al. Our strategy possesses two additional advantages: first, the first point reached from where the entire polygon P is seen is precisely the closest such point to the starting position s, and second, all the points of the path are directly determined in terms of s and of polygon vertices, which implies that an actual robot following the strategy is not expected to deviate much from its course due to numerical error. The competitiveness analysis is based on properties of the class of curves with increasing chords.
In many fault detection problems, the goal is to identify defective items from a set of items with a minimum number of tests. Each test is on a subset of items, which tells whether the subset contains a defective item...
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In many fault detection problems, the goal is to identify defective items from a set of items with a minimum number of tests. Each test is on a subset of items, which tells whether the subset contains a defective item or not. The concept of competitive algorithm has been developed to relate the properties of the group testing algorithms that assume that the number of defective items d is known, to those without any a priori knowledge on d. A new concept of strongly competitive algorithm is defined that relates different characteristics of these two classes of algorithms and present an interesting relationship between the two concepts competitive and strongly competitive. A strongly competitive algorithm is also presented.
Many fault-detection problems fall into the following model: There is a set of n items, some of which are defective. The goal is to identify the defective items by using the minimum number of tests. Each test is on a ...
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Many fault-detection problems fall into the following model: There is a set of n items, some of which are defective. The goal is to identify the defective items by using the minimum number of tests. Each test is on a subset of items and tells whether the subset contains a defective item or not. Let M(alpha) (d, n)(M. (d\n)) denote the maximum number of tests for an algorithm alpha to identify d defectives from a set of n items provided that d, the number of defective items, is known (unknown) before the testing. Let M(d, n) = min(alpha) M(alpha) (d, n). An algorithm alpha is called a competitive algorithm if there exist constants c and a such that for all n > d > 0, M(alpha)(d\n) less-than-or-equal-to cM(d, n) + alpha. This paper confirms a recent conjecture that there exists a bisecting algorithm A such that M(A)(d\n) less-than-or-equal-to 2M(d, n) + 1. Also, an algorithm B such that M(B)(d\n) less-than-or-equal-to 1.65 M(d, n) + 10 is presented.
Based on the characteristics of distrubuted system and the behavior of parallelprograms, this paper presents the fixed and randofored competitive memory coherence algorithms for distributed shared virtual memory These...
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Based on the characteristics of distrubuted system and the behavior of parallelprograms, this paper presents the fixed and randofored competitive memory coherence algorithms for distributed shared virtual memory These algorithms exploit parallel programs' locality of reference and dribit good competitive property Our simulation shows that the fixed and randomized algorithms achieve better performance and higher stability than other strategies such as write-invalldate and write-update.
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