In OSI management, we utilize a scope parameter in Common Management Information Service (CMIS) that enables us to operate multiple Managed Objects (MOs) at one CMIS operation, so that we may reduce the number of comm...
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In OSI management, we utilize a scope parameter in Common Management Information Service (CMIS) that enables us to operate multiple Managed Objects (MOs) at one CMIS operation, so that we may reduce the number of communications between a manager and an agent. The more the number of MOs increases, the harder it is to find optimal combinations of scopes. In an existing approximation algorithm for finding optimal combinations of scopes, there are restrictions on the structure of a naming tree for the algorithm to work efficiently and the lower bound of its approximation ratio, n/4, grows in proportion to the number of MOs, n. This paper proposes a new approximation algorithm that removes the restriction on the structure of a naming tree and significantly improves the approximation ratio to (1 + ln n) in the upper bound, by keeping the same time complexity as the existing algorithm.
In this paper, we study the single machine total completion scheduling problem subject to a period of maintenance. We propose an approximation algorithm to solve the problem with a worst case error bound of 3/17. Furt...
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In this paper, we study the single machine total completion scheduling problem subject to a period of maintenance. We propose an approximation algorithm to solve the problem with a worst case error bound of 3/17. Furthermore, an example is provided to show that the bound is tight. Computational experiments and an analysis are given afterwards. (C) 2003 Elsevier B.V. All rights reserved.
Self-stabilization is a theoretical framework of non-masking fault-tolerant distributed algorithms. A self-stabilizing system tolerates any kind and any finite number of transient faults, such as message loss, memory ...
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Self-stabilization is a theoretical framework of non-masking fault-tolerant distributed algorithms. A self-stabilizing system tolerates any kind and any finite number of transient faults, such as message loss, memory corruption, and topology change. Because such transient faults occur so frequently in mobile ad hoc networks, distributed algorithms on them should tolerate such events. In this paper, we propose a self-stabilizing distributed approximation algorithm for the minimum connected dominating set, which can be used, for example, as a virtual backbone or routing in mobile ad hoc networks. The size of the solution by our algorithm is at most 7.6 vertical bar D-opt vertical bar + 1.4, where D-opt is the minimum connected dominating set. The time complexity is O(k) rounds, where k is the depth of input BFS tree.
We consider the following packing problem. Let alpha be a fixed real in (0, 1]. We are given a bounding rectangle rho and a set R of n possibly intersecting unit disks whose centers lie in rho. The task is to pack a s...
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We consider the following packing problem. Let alpha be a fixed real in (0, 1]. We are given a bounding rectangle rho and a set R of n possibly intersecting unit disks whose centers lie in rho. The task is to pack a set B of m disjoint disks of radius alpha into rho such that no disk in B intersects a disk in R, where m is the maximum number of unit disks that can be packed. In this paper we present a polynomial-time algorithm for alpha = 2/3. So far only the case of packing squares has been considered. For that case, Baur and Fekete have given a polynomial-time algorithm for alpha = 2/3 and have shown that the problem cannot be solved in polynomial time for any alpha > 13/14 unless P = NP.
We study the two-machine flow shop problem with an uncapacitated interstage transporter. The jobs have to be split into batches, and upon completion on the first machine, each batch has to be shipped to the second mac...
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We study the two-machine flow shop problem with an uncapacitated interstage transporter. The jobs have to be split into batches, and upon completion on the first machine, each batch has to be shipped to the second machine by a transporter. The best known heuristic for the problem is a 3/2-approximation algorithm that outputs a two-shipment schedule. We design a 4/3-approximation algorithm that finds schedules with at most three shipments, and this ratio cannot be improved, unless schedules with more shipments are created. This improvement is achieved due to a thorough analysis of schedules with two and three shipments by means of linear programming. We formulate problems of finding an optimal schedule with two or three shipments as integer linear programs and develop strongly polynomial algorithms that find solutions to their continuous relaxations with a small number of fractional variables.
In this article, we study an approximation algorithm for the maximum edge-disjoint paths problem. In this problem, we are given a graph and a collection of pairs of vertices, and the objective is to find the maximum n...
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In this article, we study an approximation algorithm for the maximum edge-disjoint paths problem. In this problem, we are given a graph and a collection of pairs of vertices, and the objective is to find the maximum number of pairs that can be connected by edge-disjoint paths. We give an O(log n)-approximation algorithm for the maximum edge-disjoint paths problem when an input graph is either 4-edge-connected planar or Eulerian planar. This improves an O(log(2) n)-approximation algorithm given by Kleinberg [2005] for Eulerian planar graphs. Our result also generalizes the result by Chekuri et al. [2004, 2005] who gave an O(log n)-approximation algorithm for the maximum edge-disjoint paths problem with congestion two when an input graph is planar.
In this article we study the group Steiner network problem, which is defined in the following way. Given a graph G = (V,E), a partition of its vertices into K groups and connectivity requirements between the different...
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In this article we study the group Steiner network problem, which is defined in the following way. Given a graph G = (V,E), a partition of its vertices into K groups and connectivity requirements between the different groups, the aim is to find simultaneously a set of representatives, one for each group, and a minimum cost connected subgraph that satisfies the connectivity requirements between the groups (representatives). This problem is a generalization of the Steiner network problem and the group Steiner tree problem, two known NP-complete problems. We present an approximation algorithm for a special case of the group Steiner network problem with an approximation ratio of min {2(1 + 2x),2I}, where I is the cardinality of the largest-group and x is a parameter that depends on the cost function. (c) 2006 Wiley Periodicals, Inc.
Localization is a fundamental problem in robotics. The "kidnapped robot" possesses a compass and map of its environment;it must determine its location at a minimum cost of travel distance. The problem is NP-...
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Localization is a fundamental problem in robotics. The "kidnapped robot" possesses a compass and map of its environment;it must determine its location at a minimum cost of travel distance. The problem is NP-hard [G. Dudek, K. Romanik, and S. Whitesides, SIAM J. Comput., 27 (1998), pp. 583-604] even to minimize within factor c log n [C. Tovey and S. Koenig, Proceedings of the National Conference on Artificial Intelligence, Austin, TX, 2000, pp. 819-824], where n is the map size. No approximation algorithm has been known. We give an O(log(3) n)-factor algorithm. The key idea is to plan travel in a "majority-rule" map, which eliminates uncertainty and permits a link to the 1/2-Group Steiner (not Group Steiner) problem. The approximation factor is not far from optimal: we prove a c log(2-epsilon) n lower bound, assuming NP not subset of ZTIME(n(polylog(n))), for the grid graphs commonly used in practice. We also extend the algorithm to polygonal maps by discretizing the problem using novel geometric techniques.
We present a combinatorial primal-dual 7-approximation algorithm for the k-level stochastic facility location problem, the stochastic counterpart of the standard k-level facility location problem. This approximation r...
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ISBN:
(纸本)9783642143540
We present a combinatorial primal-dual 7-approximation algorithm for the k-level stochastic facility location problem, the stochastic counterpart of the standard k-level facility location problem. This approximation ratio is slightly worse than that of the primal-dual 6-approximation for the standard k-level facility location problem [3] because of the extra stochastic assumption. This new result complements the recent non-combinatorial 3-approximation algorithm for the same problem by Wang et al [21].
With the development of information and the integration of media, it has great practical significance and research value to build a digital learning environment based on the complicated electronic circuit. However, th...
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ISBN:
(纸本)9781467380386
With the development of information and the integration of media, it has great practical significance and research value to build a digital learning environment based on the complicated electronic circuit. However, the complicated electronic circuit in real-time need a complex and expensive technology. In order to overcome the high cost and technology, an approach was proposed for simplifying generation by approximating the excitations with rectangular pulses, triangular pulses and cosine waves which can be implemented with a moderate cost in analogical electronics. In this work, we improved a novel approach based on genetic programming, The differences between theoretical excitation signals and the approximation driving pulses, related to their excitation effects, were minimized by genetic programming. From these results, the accuracy of simulation can be improved by the new approach, the difference between theoretical complicated digital signals and the new approach is reduced. A tradeoff is obtained between the costs of implementation of digital processing in digital learning environments.
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