R. K. Ahuja, T. L. Magnanti, J. B. Orlin, Network Flows (Theory, Algorithms, and Applications), Prentice Hall Inc, New Jersey, 1993 (p. 448). Home/Search Document Not in Database Summary Related Articles Check |
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Achieving Near-Optimal Traffic Engineering Solutions.. - Sridharan.. (2002) (9 citations) (Correct)
....that in spite of these constraints, properly selecting OSPF weights could yield significant performance improvements. However, the paper also showed that for some topologies, performance can still be substantially different from the optimal solution. Subsequently, a result from linear programming ([5][Chap. 17, Sec. 17.2] was used in [6] to prove that any set of routes can be converted into a set of shortest paths based on some link weights, that matches or improves upon the performance of the original set of routes. This establishes that the shortest path limitation is in itself not a major ....
....impact on performance of lowering configuration overhead. Section V provides a brief summary of the paper s contributions and outline directions for future work. II. FROM OPTIMAL ROUTING TO SHORTEST PATH ROUTING In this section, we first briefly review the classic result from linear programming [5][Chap. 17, Sec. 17.2] that was cast in the context of routing in communication networks in [6] to show how optimal routing can be achieved using only shortest paths. We then discuss why this result is not directly usable in current IP networks, and finally propose solutions that allow us to ....
R. K. Ahuja, T. L. Magnanti, and J. B. Orlin, Network Flows, Chapter 17, Section 17.2. Prentice-Hall Inc., 1990.
Simulation Tools for MicroElectroMechanical Systems - Ramaswamy (2001) (1 citation) (Correct)
.... 8 9 20 0 I I I I I I I I I 0 I 2 3 4 5 6 7 8 9 Figure B I: Individual Arnoldi and Block Arnoldi comparison error in this case near s = 0 (where the reduced and the full models match best) 98 Appendix C Parameter Balancing The parameter balancing technique as described for example in [11] is useful in de termining an estimate of the minimum complexity when the cost function has mono tonically increasing and decreasing parts. Specifically let the cost function ( f( where fin) is monotonically increasing in n and g(n) is monotonically decreasing in n. Let c(n. be the ....
R.K. Ahuja, T.L. Magnanti and J.B. Orlin, Network Flows - Theory, Algorithms and Applications,Prentice-Hall Inc.,New,Jersey, 1993.
Multicast Scheduling for List Requests - Liberatore (2002) (6 citations) (Correct)
....maintains a partition of the node set and an ordering for the nodes within each partition. Initially, the node partition consists of n singleton, one for each node of the original graph. Then, our procedure computes the maximum spanning tree of the dependency graph with Kruskal s algorithm [33], and, when the algorithm combines two node sets, the heuristics also combines the two component orderings. On the whole, the algorithm is in figure 4. The algorithm is greedy, in that it arranges nodes as close as possible if there is an arc with a large weight between them. At the beginning, ....
....limited in its ability to eliminate heavy arcs. For example, suppose that the dependency graph has an arc from every node u to a designated vertex v and that the weights of the arcs e = u, v) are large, e.g. w(e) 2# n. Then, there are #(n) arcs with w(e)#(e) w(e)n #. Definition V. 2 [33]: Let G = N,A) be a directed graph. The head of an arc (u, v) is node v and the tail is node u. A method to reduce the impact of heavy arcs is to broadcast the page corresponding to the arc head soon after the tail. As a result, the arc length #(e) is reduced and so is its contribution w(e)#(e) ....
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Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin, Network flows, Prentice Hall Inc., Englewood Cliffs, NJ, 1993, Theory, algorithms, and applications.
Inverse Optimization: A Survey on Problems, Methods, and Results - Heuberger (Correct)
....[ T : u(e) 1gj jfe 2 R [ T : l(e) 1gj X v2V jP (v)j 4 jAj jV j 2 4 SOLVED INVERSE AND REVERSE PROBLEMS 13 arcs and the original set of vertices V . It is well known that this problem can be solved by strongly polynomial algorithms, we refer for instance to Ahuja, Magnanti, and Orlin [44]. When a minimal ow is calculated, the corresponding dual variables can be obtained by applying the out of kilter method starting with the optimal ow. This yields a strongly polynomial combinatorial algorithm for the solution of the inverse submodular function problem under the same hypothesis ....
R. K. Ahuja, Th. L. Magnanti, and J. B. Orlin, Network ows. Theory, algorithms, and applications, Prentice Hall Inc., Englewood Cli s, NJ, 1993.
GreenWave Routing Trees for Wireless Sensor Networks - Sivrikaya, Yener (2005) (Correct)
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R. K. Ahuja, T. L. Magnanti, J. B. Orlin, Network Flows (Theory, Algorithms, and Applications), Prentice Hall Inc, New Jersey, 1993 (p. 448).
Symmetric Cardinality Constraint with Costs - Waldemar Kocjan Per (Correct)
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Ahuja, R.K., Magnanti, T.L., Orlin, J.B.: Network flows. Theory, algorithms and applications. Prentice--Hall Inc., (1993)
Achieving Near-Optimal Traffic Engineering Solutions.. - Sridharan.. (2002) (9 citations) (Correct)
No context found.
R. K. Ahuja, T. L. Magnanti, and J. B. Orlin. Network Flows, Chapter 17, Section 17.2. Prentice-Hall Inc., 1990.
Matrix Transpose on Meshes: Theory and Practice - Kaufmann, Meyer, Sibeyn (1997) (1 citation) (Correct)
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Ahuja, R.K., T.L. Magnanti, J.B. Orlin, Network Flows, Prentice-Hall Inc., Englewood Cliffs, New Jersey, 1993.
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