An efficient algorithm for constructing a connected dominating set in mobile ad hoc networks

The connected dominating set (CDS) is widely used as a virtual backbone in mobile ad hoc networks. Although many distributed algorithms for constructing the CDS have been proposed, nearly all of them require two or more separated phases, which may cause problems such as long delay in the later phases when the network size is large. This paper proposes a Distributed Single-Phase algorithm for constructing a connected dominating set, DSP-CDS, in ad hoc networks. The DSP-CDS is an asynchronous distributed algorithm and converges quickly in a single phase. Each node uses one-hop neighborhood information and makes a local decision on whether to join the dominating set. Each node bases its decision on a key variable, strength, which guarantees that the dominating set is connected when the algorithm converges. The rules for computing strength can be changed to accommodate different application needs. The DSP-CDS adapts well to dynamic network topologies, upon which the algorithm makes only necessary local updates to maintain the CDS of the network. The performance of the DSP-CDS can be tuned by adjusting two main parameters. Extensive simulations have demonstrated that those parameters can affect the CDS size, the CDS diameter, and number of rounds for the algorithm to converge. Comparisons with other multiple-phase CDS algorithms have shown that the DSP-CDS converges fast and generates a CDS of comparable size.     

On positive influence dominating sets in social networks

In this paper, we investigate the positive influence dominating set (PIDS) which has applications in social networks. We prove that PIDS is APX-hard and propose a greedy algorithm with an approximation ratio of H(δ) where H is the harmonic function and δ is the maximum vertex degree of the graph representing a social network.     

无线网络中最小权虚拟骨干网连通部分的新方法

无线网络中的虚拟骨干(VB)是一些无线节点的子集,因此只有VB中的节点负责路由相关任务,并且VB总权值越小会导致开销越少。在一个点赋权的无线网络中,不单要考虑VB中节点数的多少,更重要的是要考虑其总权值的大小。通常,一个赋权无线网络被模型化为一个点赋权单位圆盘图(UDG),相应地赋权无线网络中的最小权VB问题被抽象为点赋权UDG中的最小权连通控制集(MWCDS)问题进行研究。求MWCDS是一个NP-难问题。为降低点赋权UDG中MWCDS问题的近似比,在连通部分提出一种新方法——基于度的点赋权Steiner树算法。结合目前最好的结果,对于UDG中的MWCDS问题将得到一个(3.32+ε)-近似算法。同样地,对于UDG中的最小权顶点覆盖(MWCVC)问题也将得到一个(3.32+ε)-近似算法。证明了通过改进连通部分的近似比令点赋权UDG中MWCDS问题的近似比降低的方法是可行的。     

Approximating minimum independent dominating sets in wireless networks

We present the first polynomial-time approximation scheme (PTAS) for the Minimum Independent Dominating Set problem in graphs of polynomially bounded growth which are used to model wireless communication networks.The approach presented yields a robust algorithm, that is, it accepts any undirected graph as input, and returns a (1+ε)-approximate minimum independent dominating set, or a certificate showing that the input graph does not satisfy the bounded growth property.     

Stackelberg Network Pricing Games

We study a multi-player one-round game termed Stackelberg Network Pricing Game, in which a leader can set prices for a subset of m priceable edges in a graph. The other edges have a fixed cost. Based on the leader’s decision one or more followers optimize a polynomial-time solvable combinatorial minimization problem and choose a minimum cost solution satisfying their requirements based on the fixed costs and the leader’s prices. The leader receives as revenue the total amount of prices paid by the followers for priceable edges in their solutions. Our model extends several known pricing problems, including single-minded and unit-demand pricing, as well as Stackelberg pricing for certain follower problems like shortest path or minimum spanning tree. Our first main result is a tight analysis of a single-price algorithm for the single follower game, which provides a (1+ε)log?m-approximation. This can be extended to provide a (1+ε)(log?k+log?m)-approximation for the general problem and k followers. The problem is also shown to be hard to approximate within $\mathcal{O}(\log^{\varepsilon}k + \log^{\varepsilon}m)$ for some ε>0. If followers have demands, the single-price algorithm provides an $\mathcal{O}(m^{2})$ -approximation, and the problem is hard to approximate within $\mathcal{O}(m^{\epsilon})$ for some ε>0. Our second main result is a polynomial time algorithm for revenue maximization in the special case of Stackelberg bipartite vertex-cover, which is based on non-trivial max-flow and LP-duality techniques. This approach can be extended to provide constant-factor approximations for any constant number of followers.     

Clustering wireless ad hoc networks with weakly connected dominating set

The increasing popular personal communications and mobile computing require a wireless network infrastructure that supports self-configuration and self-management. Efficient clustering protocol for constructing virtual backbone is becoming one of the most important issues in wireless ad hoc networks. The weakly connected dominating set   (WCDS) is very suitable for cluster formation. As finding the minimum WCDS in an arbitrary graph is a NP-Hard problem, we propose an area-based distributed algorithm for WCDS construction in wireless ad hoc networks with time and message complexity O(n)$O(n)$. This Area algorithm is divided into three phases: area partition, WCDS construction for each area and adjustment along the area borders. We confirm the effectiveness of our algorithm through analysis and comprehensive simulation study. The number of nodes in the WCDS constructed by this Area algorithm is up to around 50% less than that constructed by the previous well-known algorithm.     

Non-contractible non-edges in 2-connected graphs

Any pair of non-adjacent vertices forms a non-edge in a graph. Contraction of a non-edge merges two non-adjacent vertices into a single vertex such that the edges incident on the non-adjacent vertices are now incident on the merged vertex. In this paper, we consider simple connected graphs, hence parallel edges are removed after contraction. The minimum number of nodes whose removal disconnects the graph is the connectivity of the graph. We say a graph is k-connected, if its connectivity is k. A non-edge in a k-connected graph is contractible if its contraction does not result in a graph of lower connectivity. Otherwise the non-edge is non-contractible. We focus our study on non-contractible non-edges in 2-connected graphs. We show that cycles are the only 2-connected graphs in which every non-edge is non-contractible.     

Four-arc approximation to ellipses: The best in general

So far, the four-arc approximations to an ellipse E are made under the condition that the major and minor axes keep strictly unchanged. In general, however, this condition is unnecessary. Then the fitting can be further improved. Considering a representative quadrant of E, we first draw two auxiliary circular arcs tangent to E at the axes but having a gap ε at their boundary, such that the small arc S lies outside the large arc L. Meanwhile the extreme errors of S and L w.r.t. E are ε and −ε respectively. Giving the radii of S and L a decrement −ε/2 and an increment ε/2 brings them to join smoothly. Thus, reducing the overall error to minimum, an analytic solution in implicit form is derived.     

APX-hardness of domination problems in circle graphs

We show that the problem of finding a minimum dominating set in a circle graph is APX-hard: there is a constant δ>0 such that there is no (1+δ)-approximation algorithm for the minimum dominating set problem on circle graphs unless P=NP. Hence a PTAS for this problem seems unlikely. This hardness result complements the (2+?)-approximation algorithm for the problem [M. Damian, S.V. Pemmaraju, A (2+?)-approximation scheme for minimum domination on circle graphs, J. Algorithms 42 (2) (2002) 255-276].     

Two algorithms for minimum 2-connected r-hop dominating set

For a graph G=(V,E), a subset D⊆V is an r-hop dominating set if every vertex u∈V−D is at most r-hops away from D. It is a 2-connected r-hop dominating set if the subgraph of G induced by D is 2-connected. In this paper, we present two approximation algorithms to compute minimum 2-connected r-hop dominating set. The first one is a greedy algorithm using ear decomposition of 2-connected graphs. This algorithm is applicable to any 2-connected general graph. The second one is a three-phase algorithm which is only applicable to unit disk graphs. For both algorithms, performance ratios are given.     

连通支配集一种集中式近似算法

简单无向图的最小连通支配集问题是NP完全问题,目前还没有成熟解法。提出了一种用有序袁构建独立集求解连通支配集的算法,算法从图中度最大的顶点开始将顶点加入到有序表中,并在加入过程中构建独立集,同时加入其他节点连接独立集使其成为连通集当图中所有节点处理完成,有序表中标记为独立集的节点和连接节点就形成了一个连通支配集。实验表明算法生成的支配集较小,运行时间复杂度比较低。     

A Weakly Robust PTAS for Minimum Clique Partition in Unit Disk Graphs

We consider the problem of partitioning the set of vertices of a given unit disk graph (UDG) into a minimum number of cliques. The problem is NP-hard and various constant factor approximations are known, with the current best ratio of 3. Our main result is a weakly robust polynomial time approximation scheme (PTAS) for UDGs expressed with edge-lengths that either (i) computes a clique partition or (ii) gives a certificate that the graph is not a UDG; for the case (i) it computes a clique partition having size that is guaranteed to be within (1+ε) of the optimum size if the input is UDG; however if the input is not a UDG it either computes a clique partition as in case (i) with no guarantee on the quality of the clique partition or detects that it is not a UDG. Noting that recognition of UDG’s is NP-hard even if we are given edge lengths, our PTAS is a weakly-robust algorithm. Our algorithm can be transformed into an $O(\frac{\log^{*} n}{{\varepsilon}^{O(1)}})$ time distributed PTAS. We consider a weighted version of the clique partition problem on vertex-weighted UDGs that generalizes the problem. We note some key distinctions with the unweighted version, where ideas useful in obtaining a PTAS break down. Yet, surprisingly, it admits a (2+ε)-approximation algorithm for the weighted case where the graph is expressed, say, as an adjacency matrix. This improves on the best known 8-approximation for the unweighted case for UDGs expressed in standard form.     

A hybrid algorithmic model for the minimum weight dominating set problem

Iterated greedy algorithms belong to the class of stochastic local search methods. They are based on the simple and effective principle of generating a sequence of solutions by iterating over a constructive greedy heuristic using destruction and construction phases. This paper, first, presents an efficient randomized iterated greedy approach for the minimum weight dominating set problem, where—given a vertex-weighted graph—the goal is to identify a subset of the graphs’ vertices with minimum total weight such that each vertex of the graph is either in the subset or has a neighbor in the subset. Our proposed approach works on a population of solutions rather than on a single one. Moreover, it is based on a fast randomized construction procedure making use of two different greedy heuristics. Secondly, we present a hybrid algorithmic model in which the proposed iterated greedy algorithm is combined with the mathematical programming solver CPLEX. In particular, we improve the best solution provided by the iterated greedy algorithm with the solution polishing feature of CPLEX. The simulation results obtained on a widely used set of benchmark instances shows that our proposed algorithms outperform current state-of-the-art approaches.     

Performance evaluation for a transportation system in stochastic case

In a single-commodity multistate flow network, the arc capacity is stochastic and thus the system capacity (i.e. the maximum flow from the source to the sink) is not a fixed number. This paper constructs a multicommodity multistate flow network with weighted capacity allocation to model a transportation system. Each arc with cost attribute has several possible capacities. The capacity weight, the consumed amount of arc capacity by per commodity, varies with the arcs and types of commodity. We define the system capacity as a demand vector d if the system fulfills at most d. The addressed problem in this work is to measure the service quality of a transportation system. We propose a performance index, the probability that the upper bound of the system capacity equals a demand vector d subject to the budget constraint. A simple algorithm based on minimal cuts is presented to generate all (d,B)-MC that are the maximal capacity vectors meeting exactly the demand d under the budget B. The proposed performance index can be subsequently evaluated in terms of such (d,B)-MC.     

FINE: A Fully Informed aNd Efficient communication-induced checkpointing protocol for distributed systems

Communication-Induced Checkpointing (CIC) protocols are classified into two categories in the literature: Index-based and Model-based. In this paper, we discuss two data structures being used in these two kinds of CIC protocols, and their different roles in helping the checkpointing algorithms to enforce Z-cycle Free (ZCF) property. Then, we present our Fully Informed aNd Efficient (FINE) communication-induced checkpointing algorithm, which not only has less checkpointing overhead than the well-known Fully Informed (FI) CIC protocol proposed by Helary et al. but also has less message overhead. Performance evaluation indicates that our protocol performs better than many of the other existing CIC protocols.     

Total restrained domination in graphs

In this paper, we initiate the study of a variation of standard domination, namely total restrained domination. Let G=(V,E) be a graph. A set D⊆V is a total restrained dominating set if every vertex in V−D has at least one neighbor in D and at least one neighbor in V−D, and every vertex in D has at least one neighbor in D. The total restrained domination number of G, denoted by γ_tr(G), is the minimum cardinality of all total restrained dominating sets of G. We determine the best possible upper and lower bounds for γ_tr(G), characterize those graphs achieving these bounds and find the best possible lower bounds for where both G and are connected.     

Approximation algorithms for partially covering with edges

The edge dominating set (EDS) and edge-cover (EC) problems are classical graph covering problems in which one seeks a minimum cost collection of edges which covers the edges or vertices, respectively, of a graph. We consider the generalized partial cover version of these problems, in which failing to cover an edge, in the EDS case, or vertex, in the EC case, induces a penalty. Given a bound on the total amount of penalties that we are permitted to pay, the objective is to find a minimum cost cover with respect to this bound. We give an 8/3-approximation for generalized partial EDS. This result matches the best-known guarantee for the {0,1}-EDS problem, a specialization in which only a specified set of edges need to be covered. Moreover, 8/3 corresponds to the integrality gap of the natural formulation of the {0,1}-EDS problem. Our techniques can also be used to derive an approximation scheme for the generalized partial edge-cover problem, which is -complete even though the uniform penalty version of the partial edge-cover problem is in .     

Approximating the Sparsest k-Subgraph in Chordal Graphs

Given a simple undirected graph G = (V, E) and an integer k < |V|, the Sparsest k-Subgraph problem asks for a set of k vertices which induces the minimum number of edges. As a generalization of the classical independent set problem, Sparsest k-Subgraph is ????-hard and even not approximable unless ?????? in general graphs. Thus, we investigate Sparsest k-Subgraph in graph classes where independent set is polynomial-time solvable, such as subclasses of perfect graphs. Our two main results are the ????-hardness of Sparsest k-Subgraph on chordal graphs, and a greedy 2-approximation algorithm. Finally, we also show how to derive a P T A S for Sparsest k-Subgraph on proper interval graphs.