189 research outputs found

    Maximizing and Minimizing the Number of Generalized Colorings of Trees

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    We classify the trees on n vertices with the maximum and the minimum number of certain generalized colorings, including conflict-free, odd, non-monochromatic, star, and star rainbow vertex colorings. We also extend a result of Cutler and Radcliffe on the maximum and minimum number of existence homomorphisms from a tree to a completely looped graph on q role= presentation style= box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; font-style: normal; font-weight: normal; line-height: normal; font-size: 16.2px; text-indent: 0px; text-align: left; text-transform: none; letter-spacing: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; position: relative; q vertices

    A note on uniform power connectivity in the SINR model

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    In this paper we study the connectivity problem for wireless networks under the Signal to Interference plus Noise Ratio (SINR) model. Given a set of radio transmitters distributed in some area, we seek to build a directed strongly connected communication graph, and compute an edge coloring of this graph such that the transmitter-receiver pairs in each color class can communicate simultaneously. Depending on the interference model, more or less colors, corresponding to the number of frequencies or time slots, are necessary. We consider the SINR model that compares the received power of a signal at a receiver to the sum of the strength of other signals plus ambient noise . The strength of a signal is assumed to fade polynomially with the distance from the sender, depending on the so-called path-loss exponent Ī±\alpha. We show that, when all transmitters use the same power, the number of colors needed is constant in one-dimensional grids if Ī±>1\alpha>1 as well as in two-dimensional grids if Ī±>2\alpha>2. For smaller path-loss exponents and two-dimensional grids we prove upper and lower bounds in the order of O(logā”n)\mathcal{O}(\log n) and Ī©(logā”n/logā”logā”n)\Omega(\log n/\log\log n) for Ī±=2\alpha=2 and Ī˜(n2/Ī±āˆ’1)\Theta(n^{2/\alpha-1}) for Ī±<2\alpha<2 respectively. If nodes are distributed uniformly at random on the interval [0,1][0,1], a \emph{regular} coloring of O(logā”n)\mathcal{O}(\log n) colors guarantees connectivity, while Ī©(logā”logā”n)\Omega(\log \log n) colors are required for any coloring.Comment: 13 page

    Automatic frequency assignment for cellular telephones using constraint satisfaction techniques

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    We study the problem of automatic frequency assignment for cellular telephone systems. The frequency assignment problem is viewed as the problem to minimize the unsatisfied soft constraints in a constraint satisfaction problem (CSP) over a finite domain of frequencies involving co-channel, adjacent channel, and co-site constraints. The soft constraints are automatically derived from signal strength prediction data. The CSP is solved using a generalized graph coloring algorithm. Graph-theoretical results play a crucial role in making the problem tractable. Performance results from a real-world frequency assignment problem are presented. We develop the generalized graph coloring algorithm by stepwise refinement, starting from DSATUR and augmenting it with local propagation, constraint lifting, intelligent backtracking, redundancy avoidance, and iterative deepening

    Master index: volumes 31ā€“40

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    Optimization in Telecommunication Networks

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    Network design and network synthesis have been the classical optimization problems intelecommunication for a long time. In the recent past, there have been many technologicaldevelopments such as digitization of information, optical networks, internet, and wirelessnetworks. These developments have led to a series of new optimization problems. Thismanuscript gives an overview of the developments in solving both classical and moderntelecom optimization problems.We start with a short historical overview of the technological developments. Then,the classical (still actual) network design and synthesis problems are described with anemphasis on the latest developments on modelling and solving them. Classical results suchas Mengerā€™s disjoint paths theorem, and Ford-Fulkersonā€™s max-flow-min-cut theorem, butalso Gomory-Hu trees and the Okamura-Seymour cut-condition, will be related to themodels described. Finally, we describe recent optimization problems such as routing andwavelength assignment, and grooming in optical networks.operations research and management science;

    A randomized saturation degree heuristic for channel assignment in cellular radio networks

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    I. On a Family of Generalized Colorings. II. Some Contributions to the Theory of Neural Networks. III. Embeddings of Ultrametric Spaces

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    This thesis comprises three apparently very independent parts. However, there is a unity behind I would like to sketch very briefly. Formally graphs are in the background of most chapters and so is the duality local versus global. The first section is concerned with globally coloring graphs under some local assumptions. Algorithmically it is an intrinsically difficult task and neural networks, the topic of the second part can be used to approach intractable problems. Simple local interactions with emergent collective behavior are one of the essential features of these networks. Their current models are similar to some of those encountered in statistical mechanics, like spin glasses. In the third part, we study ultrametricity, a concept recently rediscovered by theoretical physicists in the analysis of spin-glasses. Ultrametricity can be expressed as a local constraint on the shape of each triangle of the given metric space. Unless otherwise stated, results in the first and second part are essentially original. Since the third part represents a joint work with Michael Aschbacher, Eric Baum and Richard Wilson, I should perhaps try to outline my contribution though paternity of collective results is somewhat fuzzy. While working on neural networks and spin glasses Eric and I got interested in ultrametricity. Several of us had found an initial polynomial upper bound, but the final results of "n + 1" was first reached independently by Michael and Richard. I think I obtained the theorems: 4.5, 6.1, 6.3 (using an idea of Eric), 6.4, 6.5, 6.6, 6.7 (with Richard and helpful references from Bruce Rothschild and Olga Taussky) and participated in some other results.</p

    Broadcast Scheduling in Interference Environment

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    Broadcast is a fundamental operation in wireless networks, and naiĀØve flooding is not practical, because it cannot deal with interference. Scheduling is a good way of avoiding interference, but previous studies on broadcast scheduling algorithms all assume highly theoretical models such as the unit disk graph model. In this work, we reinvestigate this problem by using the 2-Disk and the signal-to-interference-plus-noise-ratio (SINR) models. We first design a constant approximation algorithm for the 2-Disk model and then extend it to the SINR model. This result, to the best of our knowledge, is the first result on broadcast scheduling algorithms in the SINR model
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