Approximating minimum power edge-multi-covers

Nachshon Cohen, Zeev Nutov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Given a graph with edge costs, the power of a node is the maximum cost of an edge incident to it, and the power of a graph is the sum of the powers of its nodes. Motivated by applications in wireless networks, we consider the following fundamental problem in wireless network design. Given a graph G = (V,E) with edge costs and degree bounds {r(v):v ∈ V}, the Minimum-Power Edge-Multi-Cover (MPEMC) problem is to find a minimum-power subgraph J of G such that the degree of every node v in J is at least r(v). Let k = max v ∈ V r(v). For k = Ω(logn), the previous best approximation ratio for MPEMC was O(logn), even for uniform costs [3]. Our main result improves this ratio to O(logk) for general costs, and to O(1) for uniform costs. This also implies ratios O(logk) for the Minimum-Power k -Outconnected Subgraph and O(log k log n/n-k) for the Minimum-Power k -Connected Subgraph problems; the latter is the currently best known ratio for the min-cost version of the problem. In addition, for small values of k, we improve the previously best ratio k + 1 to k + 1/2.

Original languageEnglish
Title of host publicationComputer Science - Theory and Applications - 7th International Computer Science Symposium in Russia, CSR 2012, Proceedings
Number of pages12
StatePublished - 2012
Event7th International Computer Science Symposium in Russia on Computer Science - Theory and Applications, CSR 2012 - Nizhny Novgorod, Russian Federation
Duration: 3 Jul 20127 Jul 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7353 LNCS


Conference7th International Computer Science Symposium in Russia on Computer Science - Theory and Applications, CSR 2012
Country/TerritoryRussian Federation
CityNizhny Novgorod

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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