Search results for "NETWORKS"

showing 10 items of 3260 documents

An exact algorithm for the min-cost network containment problem

2004

A network design problem which arises in the distribution of a public utility provided by several competitive suppliers is studied. The problem addressed is that of determining minimum-cost (generalized) arc capacities in order to accommodate any demand between given source–sink pairs of nodes, where demands are assumed to fall within predetermined ranges. Feasible flows are initially considered as simply bounded by the usual arc capacity constraints. Then, more general linear constraints are introduced which may limit the weighted sum of the flows on some subsets of arcs. An exact cutting plane algorithm is presented for solving both of the above cases and some computational results are re…

Mathematical optimizationComputer Networks and Communicationsnetwork designpolyhedra containmentArc (geometry)Network planning and designPolyhedronExact algorithmDistribution (mathematics)Hardware and ArchitectureBounded functionLimit (mathematics)max weight directed cutSoftwareCutting-plane methodInformation SystemsMathematicsNetworks
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Performance modeling of epidemic routing

2006

In this paper, we develop a rigorous, unified framework based on ordinary differential equations (ODEs) to study epidemic routing and its variations. These ODEs can be derived as limits of Markovian models under a natural scaling as the number of nodes increases. While an analytical study of Markovian models is quite complex and numerical solution impractical for large networks, the corresponding ODE models yield closed-form expressions for several performance metrics of interest, and a numerical solution complexity that does not increase with the number of nodes. Using this ODE approach, we investigate how resources such as buffer space and the number of copies made for a packet can be tra…

Mathematical optimizationComputingMethodologies_SIMULATIONANDMODELINGComputer Networks and CommunicationsDifferential equationComputer scienceWireless ad hoc networkNetwork packetNumerical analysisMathematicsofComputing_NUMERICALANALYSISOdeMarkov processMarkov modelsymbols.namesakeOrdinary differential equationMetric (mathematics)symbolsRouting (electronic design automation)ScalingSimulation
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The stacker crane problem and the directed general routing problem

2015

[EN] This article deals with the polyhedral description and the resolution of the directed general routing problem (DGRP) and the stacker crane problem (SCP). The DGRP contains a large number of important arc and node routing problems as special cases, including the SCP. Large families of facet-defining inequalities for the DGRP are described and a branch-and-cut algorithm for these problems is presented. Extensive computational experiments over different sets of DGRP and SCP instances are included.

Mathematical optimizationDirected general routing problemStacker crane problemComputer Networks and CommunicationsStackerNode (networking)Branch-and-cut algorithmDirected graphResolution (logic)Directed rural postman problemHardware and ArchitectureRouting (electronic design automation)MATEMATICA APLICADASoftwareInformation SystemsMathematics
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Multicell power allocation method based on game theory for inter-cell interference coordination

2009

As a new technology, coordinated multipoint (CoMP) transmission is included in LTE-Advanced study item. Moreover, the network architecture in LTE-Advanced system is modified to take into account coordinated transmission. Under this background, a novel power allocation game model is established to mitigate inter-cell interference with cellular coordination. In the light of cellular cooperation relationship and centralized control in eNodeB, the power allocation in each served antenna unit aims to make signal to interference plus noise ratio (SINR) balanced among inter-cells. Through the proposed power allocation game algorithm, the users' SINR can reach the Nash equilibrium, making it feasib…

Mathematical optimizationGeneral Computer ScienceComputer scienceComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSSignal-to-interference-plus-noise ratioThroughputInterference (wave propagation)Blocking (statistics)Telecomunicaciósymbols.namesakeEnodeBTransmission (telecommunications)Nash equilibriumsymbolsGame theoryComunicació i tecnologiaSimulation
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On the approximability of the range assignment problem on radio networks in presence of selfish agents

2005

AbstractWe consider the range assignment problem in ad-hoc wireless networks in the context of selfish agents: A network manager aims to assigning transmission ranges to the stations in order to achieve strong connectivity of the network within a minimal overall power consumption. Station is not directly controlled by the manager and may refuse to transmit with a certain transmission range because it might be costly in terms of power consumption.We investigate the existence of payment schemes which induce the stations to follow the decisions of a network manager in computing a range assignment, that is, truthful mechanisms for the range assignment problem. We provide both positive and negat…

Mathematical optimizationGeneral Computer ScienceSettore INF/01 - Informaticabusiness.industryWireless networkApproximation algorithmContext (language use)Approximation algorithmsTheoretical Computer ScienceNetwork managementAlgorithmic mechanism design; Energy consumption in wireless networks; Approximation algorithmsEnergy consumption in wireless networksalgorithmic mechanism design; approximation algorithms; energy consumption in wireless networksbusinessTime complexityAssignment problemAlgorithmConnectivityAlgorithmic mechanism designAlgorithmic mechanism designMathematicsComputer Science(all)Theoretical Computer Science
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Determining the Difficulty of Landscapes by PageRank Centrality in Local Optima Networks

2016

The contribution of this study is twofold: First, we show that we can predict the performance of Iterated Local Search (ILS) in different landscapes with the help of Local Optima Networks (LONs) with escape edges. As a predictor, we use the PageRank Centrality of the global optimum. Escape edges can be extracted with lower effort than the edges used in a previous study. Second, we show that the PageRank vector of a LON can be used to predict the solution quality (average fitness) achievable by ILS in different landscapes.

Mathematical optimizationIterated local searchbusiness.industrymedia_common.quotation_subject02 engineering and technologyMachine learningcomputer.software_genreLocal optima networkslaw.inventionGlobal optimumPageRanklaw020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingQuality (business)Artificial intelligencebusinessCentralitycomputerMathematicsmedia_common
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Achieving Fair Load Balancing by Invoking a Learning Automata-Based Two-Time-Scale Separation Paradigm.

2020

Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. In this article, we consider the problem of load balancing (LB), but, unlike the approaches that have been proposed earlier, we attempt to resolve the problem in a fair manner (or rather, it would probably be more appropriate to describe it as an ε-fair manner because, although the LB…

Mathematical optimizationLearning automataComputer Networks and Communicationsbusiness.industryStochastic processComputer scienceQuality of serviceResource allocationsCloud computingLoad balancing (computing)Continuous learning automatonsComputer Science ApplicationsArtificial IntelligenceServerResource allocationFair load balancingbusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550SoftwareIEEE transactions on neural networks and learning systems
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Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation

2011

Part 1: - PE-CRN 2011 Workshop; International audience; In cognitive radio networks, channel aggregation techniques which aggregate several channels together as one channel have been proposed in many MAC protocols. In this paper, we consider elastic data traffic and spectrum adaptation for channel aggregation, and propose two new strategies named as Greedy and Dynamic respectively. The performance of channel aggregation represented by these strategies is evaluated using continuous time Markov chain models. Moreover, simulation results based on various traffic distributions are utilized in order to evaluate the validity and preciseness of the mathematical models.

Mathematical optimizationMathematical modelComputer science020209 energycontinuous time Markov chain modelsAggregate (data warehouse)Cognitive radio networks020206 networking & telecommunications02 engineering and technologyMarkov modelchannel aggregation strategyperformance evaluationContinuous-time Markov chain[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]Cognitive radio0202 electrical engineering electronic engineering information engineeringDynamic channel[INFO]Computer Science [cs]SimulationComputer Science::Information TheoryCommunication channel
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Developing Domain-Knowledge Evolutionary Algorithms for Network-on-Chip Application Mapping

2013

This paper addresses the Network-on-Chip (NoC) application mapping problem. This is an NP-hard problem that deals with the optimal topological placement of Intellectual Property cores onto the NoC tiles. Network-on-Chip application mapping Evolutionary Algorithms are developed, evaluated and optimized for minimizing the NoC communication energy. Two crossover and one mutation operators are proposed. It is analyzed how each optimization algorithm performs with every genetic operator, in terms of solution quality and convergence speed. Our proposed operators are compared with state-of-the-art genetic operators for permutation problems. Finally, the problem is approached in a multi-objective w…

Mathematical optimizationMutation operatorTheoretical computer scienceComputer Networks and CommunicationsComputer scienceQuality control and genetic algorithmsCrossoverEvolutionary algorithmGenetic operatorMulti-objective optimizationNetwork on a chipArtificial IntelligenceHardware and ArchitectureSimulated annealingGenetic algorithmGenetic representationSoftwareMicroprocessors and Microsystems
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Joint Optimization of Detection Threshold and Resource Allocation in Infrastructure-based Multi-band Cognitive Radio Networks

2012

[EN] Consider an infrastructure-based multi-band cognitive radio network (CRN) where secondary users (SUs) opportunistically access a set of sub-carriers when sensed as idle. The carrier sensing threshold which affects the access opportunities of SUs is conventionally regarded as static and treated independently from the resource allocation in the model. In this article, we study jointly the optimization of detection threshold and resource allocation with the goal of maximizing the total downlink capacity of SUs in such CRNs. The optimization problem is formulated considering three sets of variables, i.e., detection threshold, sub-carrier assignment and power allocation, with constraints on…

Mathematical optimizationOptimization problemComputer scienceComputer Networks and Communications020208 electrical & electronic engineeringReal-time computing020206 networking & telecommunications02 engineering and technologyINGENIERIA TELEMATICAPower budgetComputer Science ApplicationsMulti-band cognitive radio networksBase stationCognitive radioTelecommunications linkSignal Processing0202 electrical engineering electronic engineering information engineeringResource allocationOnline algorithmResource allocationOptimization of detection threshold
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