Minimizing the sum of distances to a server in a constraint network

被引:1
|
作者
Carmi, Paz
Chaitman-Yerushalmi, Lilach
Ozeri, Bat-Chen
机构
关键词
Computational geometry; MINIMUM SPANNING-TREES;
D O I
10.1016/j.comgeo.2019.01.003
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper deals with constructing centralized geometric network that represents a set of clients that need to be connected to a server. We consider the problem of minimizing the sum of the shortest paths from the clients to the server in the network, subject to some constraints. We refer to this summation as the network cost. The motivation for this work was derived from the combination of centralized communication network and geometric sink spanner. Formally, given a set V of points (representing clients) in the plane, a special point q is an element of V (representing a server), a real number w > 0 (the network weight bound), and an integer h >= 1 (the hop bound), the goal is to construct a directed network G = (V, E) of minimum cost, such that there is a directed path from every point in V to q with at most h hops, and Sigma((v,u)is an element of E) vertical bar vu vertical bar <= w, where I vu I denotes the Euclidean distance between v and u. In this paper we start by establishing a connection between the considered problem and geometric sink spanner network. Then, we present our main result, a bi-criteria approximation algorithm, that approximates both the weight and the cost of the network with respect to an optimal network, in (vertical bar V vertical bar/epsilon)(0(h/epsilon)). More precisely, we construct a network such that its cost (i.e., sum of the shortest paths from every v is an element of V to q) is at most (1 + h epsilon) times the cost of an optimal network and its weight (i.e., Sigma((v,u)is an element of E) vertical bar vu vertical bar) is at most (1 + epsilon).w, for any > 0. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 12
页数:12
相关论文
共 50 条
  • [31] On the Minkowski distances and products of sum sets
    Oliver Roche-Newton
    Misha Rudnev
    Israel Journal of Mathematics, 2015, 209 : 507 - 526
  • [32] SUM OF DISTANCES BETWEEN POINTS ON A SPHERE
    ALEXANDER, R
    ACTA MATHEMATICA ACADEMIAE SCIENTIARUM HUNGARICAE, 1972, 23 (3-4): : 443 - 448
  • [33] Minimizing a sum of clipped convex functions
    Barratt, Shane
    Angeris, Guillermo
    Boyd, Stephen
    OPTIMIZATION LETTERS, 2020, 14 (08) : 2443 - 2459
  • [34] Learning by Minimizing the Sum of Ranked Range
    Hu, Shu
    Ying, Yiming
    Wang, Xin
    Lyu, Siwei
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 33, NEURIPS 2020, 2020, 33
  • [35] Minimizing the sum of many rational functions
    Bugarin F.
    Henrion D.
    Lasserre J.B.
    Mathematical Programming Computation, 2016, 8 (01) : 83 - 111
  • [36] ESTIMATION OF MINIMIZING SUM OF ABSOLUTE ERRORS
    TAYLOR, LD
    ECONOMETRICA, 1971, 39 (04) : 231 - &
  • [37] ON MINIMIZING THE SUM OF K-TARDINESSES
    WOEGINGER, G
    INFORMATION PROCESSING LETTERS, 1991, 38 (05) : 253 - 256
  • [38] MINIMIZING THE SUM TOTAL OF ALL RISKS
    WIESNER, L
    ATOMWIRTSCHAFT-ATOMTECHNIK, 1979, 24 (03): : 145 - 150
  • [39] Minimizing a sum of clipped convex functions
    Shane Barratt
    Guillermo Angeris
    Stephen Boyd
    Optimization Letters, 2020, 14 : 2443 - 2459
  • [40] Approximation of belief functions by minimizing Euclidean distances
    Weiler, T
    Bodenhofer, U
    SOFT METHODS IN PROBABILITY, STATISTICS AND DATA ANALYSIS, 2002, : 170 - 177