Topological Design of Multipoint Teleprocessing Networks

Elias, Demetra; Ferguson, Michael J.

doi:10.1109/tcom.1974.1092122

Cited by 40 publications

(13 citation statements)

References 5 publications

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“…The equal weight CMST problem can be employed for finding the capacity constrained execution plan. We employ an approximate algorithm [9] to obtain the execution plan efficiently. The existence of the dummy node again guarantees that the SD-graph can always produce such a plan.…”

Section: Capacity Constrained Execution Planmentioning

confidence: 99%

Efficient execution plans for distributed skyline query processing

Rocha-Junior

Vlachou

Doulkeridis

et al. 2011

Proceedings of the 14th International Conference on Extending Database Technology

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In this paper, we study the generation of efficient execution plans for skyline query processing in large-scale distributed environments. In such a setting, each server stores autonomously a fraction of the data, thus all servers need to process the skyline query. An execution plan defines the order in which the individual skyline queries are processed on different servers, and influences the performance of query processing. Querying servers consecutively reduces the amount of transferred data and the number of queried servers, since skyline points obtained by one server prune points in the subsequent servers, but also increases the latency of the system. To address this trade-off, we introduce a novel framework, called SkyPlan, for processing distributed skyline queries that generates execution plans aiming at optimizing the performance of query processing. Thus, we quantify the gain of querying consecutively different servers. Then, execution plans are generated that maximize the overall gain, while also taking into account additional objectives, such as bounding the maximum number of hops required for the query or balancing the load on different servers fairly. Finally, we present an algorithm for distributed processing based on the generated plan that continuously refines the execution plan during in-network processing. Our framework consistently outperforms the state-of-the-art algorithm.

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Section: Capacity Constrained Execution Planmentioning

confidence: 99%

Efficient execution plans for distributed skyline query processing

Rocha-Junior

Vlachou

Doulkeridis

et al. 2011

Proceedings of the 14th International Conference on Extending Database Technology

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“…The process is repeated until no further improvement is possible. By contrast, the constructive method of Elias and Ferguson (1974) begins with a solution for the MST relaxation of the CMST and iteratively attempts to satisfy each of the capacity constraints using the minimum increase in cost. This heuristic was later used by Gavish (1983) as a heuristic projection method for a Lagrangian relaxation approach.…”

Section: Previous Approaches For Cmstmentioning

confidence: 99%

“…Such cycles are eliminated by closing the most expensive arc in a cycle and connecting the corresponding set of nodes to the root by an arc of minimum cost. Finally, the capacity constraints are satisfied by using a method analogous to that by Elias and Ferguson (1974). The sub-trees that violate capacity constraints are iteratively fixed.…”

Section: Projectionmentioning

confidence: 99%

RAMP for the capacitated minimum spanning tree problem

2010

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This paper introduces dual and primal-dual RAMP algorithms for the solution of the capacitated minimum spanning tree problem (CMST). A surrogate constraint relaxation incorporating cutting planes is proposed to explore the dual solution space. In the dual RAMP approach, primal-feasible solutions are obtained by simple tabu searches that project dual solutions onto primal feasible space. A primal-dual approach is achieved by including a scatter search procedure that further exploits the adaptive memory framework. Computational results from applying the methods to a standard set of benchmark problems disclose that the dual RAMP algorithm finds high quality solutions very efficiently and that its primal-dual enhancement is still more effective.

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“…The approximation ratio of such an approach would be 4(1 − 1 k ) 2 + 1. There are several exact algorithms and mathematical formulations [Chandy and Lo 1973;Chandy and Russell 1972;Elias and Ferguson 1974;Gavish 1982Gavish , 1983Gavish , 1985Gouveia 1993Gouveia , 1995Gouveia and Ao 1991;Hall 1996;Kershenbaum and Boorstyn 1983;Malik and Yu 1993] available for solving the CMST problem. The instance sizes that can be solved by these algorithms to optimality, in reasonable amount of time, are still far from that of real-time instances.…”

Section: Introductionmentioning

confidence: 99%

“…Esau and Williams [1966] gave an efficient and well-known savings heuristic for the CMST problem. Some of the other heuristics that use savings procedure to construct the tree include Elias and Ferguson [1974], Gavish [1991], Gavish and Altinkemer [1986], Kershenbaum [1974], Whitney [1970]. Construction procedures [Boorstyn and Frank 1977;Chandy and Russell 1972;Karnaugh 1976;Kershenbaum and Chou 1974;Martin 1967;McGregor and Shen 1977;Schneider and Zastrow 1982;Sharma and El-Bardai 1970] start with an empty tree and add the best edge or node to grow the tree.…”

Section: Introductionmentioning

confidence: 99%

Approximation algorithms for the capacitated minimum spanning tree problem and its variants in network design

Jothi

Raghavachari

2005

ACM Trans. Algorithms

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Given an undirected graph G = (V, E) with nonnegative costs on its edges, a root node r ∈ V , a set of demands D ⊆ V with demand v ∈ D wishing to route w(v) units of flow (weight) to r , and a positive number k, the Capacitated Minimum Steiner Tree (CMStT) problem asks for a minimum Steiner tree, rooted at r , spanning the vertices in D ∪ {r }, in which the sum of the vertex weights in every subtree connected to r is at most k. When D = V , this problem is known as the Capacitated Minimum Spanning Tree (CMST) problem. Both CMsT and CMST problems are NP-hard. In this article, we present approximation algorithms for these problems and several of their variants in network design. Our main results are the following:-We present a (γρ ST + 2)-approximation algorithm for the CMStT problem, where γ is the inverse Steiner ratio, and ρ ST is the best achievable approximation ratio for the Steiner tree problem. Our ratio improves the current best ratio of 2ρ ST + 2 for this problem. -In particular, we obtain (γ +2)-approximation ratio for the CMST problem, which is an improvement over the current best ratio of 4 for this problem. For points in Euclidean and rectilinear planes, our result translates into ratios of 3.1548 and 3.5, respectively. -For instances in the plane, under the L p norm, with the vertices in D having uniform weights, we present a nontrivial ( 7 5 ρ ST + 3 2 )-approximation algorithm for the CMStT problem. This translates into a ratio of 2.9 for the CMST problem with uniform vertex weights in the L p metric plane. Our

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Topological Design of Multipoint Teleprocessing Networks

Cited by 40 publications

References 5 publications

Efficient execution plans for distributed skyline query processing

Efficient execution plans for distributed skyline query processing

RAMP for the capacitated minimum spanning tree problem

Approximation algorithms for the capacitated minimum spanning tree problem and its variants in network design

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