5 research outputs found

    Approximation Algorithm for Minimum Weight Connected mm-Fold Dominating Set

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    Using connected dominating set (CDS) to serve as a virtual backbone in a wireless networks can save energy and reduce interference. Since nodes may fail due to accidental damage or energy depletion, it is desirable that the virtual backbone has some fault-tolerance. A kk-connected mm-fold dominating set ((k,m)(k,m)-CDS) of a graph GG is a node set DD such that every node in VDV\setminus D has at least mm neighbors in DD and the subgraph of GG induced by DD is kk-connected. Using (k,m)(k,m)-CDS can tolerate the failure of min{k1,m1}\min\{k-1,m-1\} nodes. In this paper, we study Minimum Weight (1,m)(1,m)-CDS problem ((1,m)(1,m)-MWCDS), and present an (H(δ+m)+2H(δ1))(H(\delta+m)+2H(\delta-1))-approximation algorithm, where δ\delta is the maximum degree of the graph and H()H(\cdot) is the Harmonic number. Notice that there is a 1.35lnn1.35\ln n-approximation algorithm for the (1,1)(1,1)-MWCDS problem, where nn is the number of nodes in the graph. Though our constant in O(ln)O(\ln \cdot) is larger than 1.35, nn is replaced by δ\delta. Such a replacement enables us to obtain a (6.67+ε)(6.67+\varepsilon)-approximation for the (1,m)(1,m)-MWCDS problem on unit disk graphs

    Approximation Algorithm for Minimum Weight (k,m)(k,m)-CDS Problem in Unit Disk Graph

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    In a wireless sensor network, the virtual backbone plays an important role. Due to accidental damage or energy depletion, it is desirable that the virtual backbone is fault-tolerant. A fault-tolerant virtual backbone can be modeled as a kk-connected mm-fold dominating set ((k,m)(k,m)-CDS for short). In this paper, we present a constant approximation algorithm for the minimum weight (k,m)(k,m)-CDS problem in unit disk graphs under the assumption that kk and mm are two fixed constants with mkm\geq k. Prior to this work, constant approximation algorithms are known for k=1k=1 with weight and 2k32\leq k\leq 3 without weight. Our result is the first constant approximation algorithm for the (k,m)(k,m)-CDS problem with general k,mk,m and with weight. The performance ratio is (α+2.5kρ)(\alpha+2.5k\rho) for k3k\geq 3 and (α+2.5ρ)(\alpha+2.5\rho) for k=2k=2, where α\alpha is the performance ratio for the minimum weight mm-fold dominating set problem and ρ\rho is the performance ratio for the subset kk-connected subgraph problem (both problems are known to have constant performance ratios.

    Constant-approximation algorithms for highly connected multi-dominating sets in unit disk graphs

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    Given an undirected graph on a node set VV and positive integers kk and mm, a kk-connected mm-dominating set ((k,m)(k,m)-CDS) is defined as a subset SS of VV such that each node in VSV \setminus S has at least mm neighbors in SS, and a kk-connected subgraph is induced by SS. The weighted (k,m)(k,m)-CDS problem is to find a minimum weight (k,m)(k,m)-CDS in a given node-weighted graph. The problem is called the unweighted (k,m)(k,m)-CDS problem if the objective is to minimize the cardinality of a (k,m)(k,m)-CDS. These problems have been actively studied for unit disk graphs, motivated by the application of constructing a virtual backbone in a wireless ad hoc network. However, constant-approximation algorithms are known only for k3k \leq 3 in the unweighted (k,m)(k,m)-CDS problem, and for (k,m)=(1,1)(k,m)=(1,1) in the weighted (k,m)(k,m)-CDS problem. In this paper, we consider the case in which mkm \geq k, and we present a simple O(5kk!)O(5^k k!)-approximation algorithm for the unweighted (k,m)(k,m)-CDS problem, and a primal-dual O(k2logk)O(k^2 \log k)-approximation algorithm for the weighted (k,m)(k,m)-CDS problem. Both algorithms achieve constant approximation factors when kk is a fixed constant

    A PTAS for the Weighted Unit Disk Cover Problem

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    We are given a set of weighted unit disks and a set of points in Euclidean plane. The minimum weight unit disk cover (\UDC) problem asks for a subset of disks of minimum total weight that covers all given points. \UDC\ is one of the geometric set cover problems, which have been studied extensively for the past two decades (for many different geometric range spaces, such as (unit) disks, halfspaces, rectangles, triangles). It is known that the unweighted \UDC\ problem is NP-hard and admits a polynomial-time approximation scheme (PTAS). For the weighted \UDC\ problem, several constant approximations have been developed. However, whether the problem admits a PTAS has been an open question. In this paper, we answer this question affirmatively by presenting the first PTAS for \UDC. Our result implies the first PTAS for the minimum weight dominating set problem in unit disk graphs. Combining with existing ideas, our result can also be used to obtain the first PTAS for the maxmimum lifetime coverage problem and an improved constant approximation ratio for the connected dominating set problem in unit disk graphs.Comment: We fixed several typos in this version. 37 pages. 15 figure

    Adaptive Algorithm for Finding Connected Dominating Sets in Uncertain Graphs

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    The problem of finding a minimum-weight connected dominating set (CDS) of a given undirected graph has been studied actively, motivated by operations of wireless ad hoc networks. In this paper, we formulate a new stochastic variant of the problem. In this problem, each node in the graph has a hidden random state, which represents whether the node is active or inactive, and we seek a CDS of the graph that consists of the active nodes. We consider an adaptive algorithm for this problem, which repeat choosing nodes and observing the states of the nodes around the chosen nodes until a CDS is found. Our algorithms have a theoretical performance guarantee that the sum of the weights of the nodes chosen by the algorithm is at most O(αlog(1/δ))O(\alpha \log (1/\delta)) times that of any adaptive algorithm in expectation, where α\alpha is an approximation factor for the node-weighted polymatroid Steiner tree problem and δ\delta is the minimum probability of possible scenarios on the node states.Comment: This is the accepted version of a paper to be published by IEEE/ACM Transactions on Networkin
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