Search results for "Consensus protocol"

showing 10 items of 18 documents

Distributed Consensus in Networks of Dynamic Agents

2006

Stationary and distributed consensus protocols for a network of n dynamic agents under local information is considered. Consensus must be reached on a group decision value returned by a function of the agents' initial state values. As a main contribution we show that the agents can reach consensus if the value of such a function computed over the agents' state trajectories is time invariant. We use this basic result to introduce a protocol design rule allowing consensus on a quite general set of values. Such a set includes, e.g., any generalized mean of order p of the agents' initial states. We demonstrate that the asymptotical consensus is reached via a Lyapunov approach. Finally we perfor…

Asymptotic stability; Distributed consensus protocolsEngineeringMathematical optimizationAsymptotic stabilitybusiness.industryFunction (mathematics)Network topologyUniform consensusComputer Science::Multiagent SystemsLTI system theorySet (abstract data type)Distributed consensus protocolsConsensusExponential stabilityComputer Science::Systems and ControlControl theoryexperimental mechanics Fourier transform load stepping photoelasticityGeneralized meanbusinessProceedings of the 44th IEEE Conference on Decision and Control
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Lazy consensus for networks with unknown but bounded disturbances

2007

We consider stationary consensus protocols for networks of dynamic agents. The measure of the neighbors' state is affected by Unknown But Bounded disturbances. Here the main contribution is the formulation and solution of what we call the isin-consensus problem, where the states are required to converge in a tube of ray isin asymptotically or in finite time.

Computer Science::Multiagent SystemsDynamic agentsLazy consensusComputer scienceControl theoryMulti-agent systemBounded functionDynamic agents; Lazy consensus; Stationary consensus protocolsState (functional analysis)Stationary consensus protocolsTopologyMeasure (mathematics)Uniform consensus2007 46th IEEE Conference on Decision and Control
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Quantized Dissensus in Networks of Agents subject to Death and Duplication

2012

Dissensus is a modeling framework for networks of dynamic agents in competition for scarce resources. Originally inspired by biological cells behaviors, it fits also marketing, finance and many other application areas. Competition is often unstable in the sense that strong agents, those having access to large resources, gain more and more resources at the expense of weak agents. Thus, strong agents duplicate when reaching a critical amount of resources, whereas weak agents die when loosing all their resources. To capture all these phenomena we introduce systems with a discrete time gossip and unstable state dynamics interrupted by discrete events affecting the network topology. Invariancy o…

Dynamic ProgrammingConsensus ProtocolsComputer sciencemedia_common.quotation_subjectDistributed computingSubject (philosophy)Dynamical Systems (math.DS)Network topologyConsensus protocolScarcityCompetition (economics)Settore ING-INF/04 - AutomaticaGossipFOS: MathematicsElectrical and Electronic EngineeringMathematics - Dynamical SystemsMathematics - Optimization and Controlmedia_commonConsensus Protocols; Quantized Control; Dynamic Programming; Network based marketing; Dynamic Pie Diagram.Dynamic Pie Diagramquantized controlComputer Science ApplicationsConsensus protocolsConsensus protocols; network based marketing; quantized controlDiscrete time and continuous timeControl and Systems Engineeringnetwork based marketingOptimization and Control (math.OC)90C3993Dxx34K2034a38Settore MAT/09 - Ricerca Operativa
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Quantized Dissensus in switching networks with nodes death and duplication

2009

Hybrid systemsswitching systemsHybrid systems switching systems consensus protocol quantized protocolquantized protocolHybrid systems; switching systems; consensus protocol; quantized protocolconsensus protocol
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Dissensus, death and division

2009

The modeling of switching systems describing networks where death and duplication processes occur is described. A dissensus protocol, complementary to consensus protocol, is introduced and the convergence or divergence of the agents' state evolution is studied. We discuss some properties of the topology reached by the network when different rules of duplication and inheritance are implemented.

Impulsive networksHybrid systemsComputer scienceDistributed computingconsnesus problemsSwitching systemsDivision (mathematics)biological modelDivergence (computer science)Consensus protocolsInheritance (object-oriented programming)Settore ING-INF/04 - Automaticaconsnesus problems biological model networksnetworksConvergence (routing)Settore MAT/09 - Ricerca OperativaProtocol (object-oriented programming)Biological models; Consensus protocols; Hybrid systems; Impul-sive networks; Switching systems;Biological models; Consensus protocols; Hybrid systems; Impulsive networks; Switching systemsBiological models2009 American Control Conference
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Cooperative Inventory control

2005

In multi-retailer inventory control the possibility of sharing setup costs motivates communication and coordination among the retailers. We solve the problem of finding suboptimal distributed reordering policies that minimize setup, ordering, storage, and shortage costs incurred by the retailers over a finite horizon. Neuro-dynamic programming (NDP) reduces the computational complexity of the solution algorithm from exponential to polynomial on the number of retailers.

Inventory controlConsensus protocol; Inventory level; Nash equilibrium; Setup cost; Supply chain;Inventory levelPolynomialMathematical optimizationComputational complexity theoryComputer scienceSetup costSupply chainEconomic shortageFinite horizonSupply chainConsensus protocolNash equilibriumExponential functionComputingMilieux_GENERALsymbols.namesakeNash equilibriumsymbols
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Non-linear protocols for optimal distributed consensus in networks of dynamic agents

2006

We consider stationary consensus protocols for networks of dynamic agents with fixed topologies. At each time instant, each agent knows only its and its neighbors'' state, but must reach consensus on a group decision value that is function of all the agents'' initial state. We show that the agents can reach consensus if the value of such a function is time-invariant when computed over the agents'' state trajectories. We use this basic result to introduce a non-linear protocol design rule allowing consensus on a quite general set of values. Such a set includes, e.g., any generalized mean of order p of the agents'' initial states. As a second contribution we show that our protocol design is t…

Lyapunov functionMathematical optimizationDecentralized controlGeneral Computer ScienceConsensus protocols; Decentralized control; Networks; Optimal controlUniform consensussymbols.namesakeConsensusComputer Science::Systems and ControlElectrical and Electronic EngineeringMathematicsMechanism designSupervisorbusiness.industryMechanical EngineeringRational agentDecentralised systemOptimal controlComputer Science::Multiagent SystemsConsensus protocolsControl and Systems EngineeringsymbolsArtificial intelligenceSettore MAT/09 - Ricerca OperativaNetworksbusinessGame theorySystems & Control Letters
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Dealing with uncertainty in consensus protocols

2009

Recent results on consensus protocols for networks are presented. The basic tools and the main contribution available in the literature are considered, together with some of the related challenging aspects: estimation in networks and how to deal with disturbances is considered. Motivated by applications to sensor, peer-to-peer, and ad hoc networks, many papers have considered the problem of estimation in a consensus fashion. Here, the Unknown But Bounded (UBB) noise affecting the network is addressed in details. Because of the presence of UBB disturbances convergence to equilibria with all equal components is, in general, not possible. The solution of the e-consensus problem, where the stat…

Mathematical optimizationConsensusWireless ad hoc networkComputer scienceDistributed computingBounded functionConvergence (routing)Consensus protocol; optimizazion; disturbancesNoise (video)Laplacian matrixFocus (optics)Uniform consensus
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MECHANISM DESIGN FOR OPTIMAL CONSENSUS PROBLEMS

2006

We consider stationary consensus protocols for networks of dynamic agents with fixed and switching topologies. At each time instant, each agent knows only its and its neighbors’ state, but must reach consensus on a group decision value that is function of all the agents’ initial state.We show that our protocol design is the solution of individual optimizations performed by the agents. This notion suggests a game theoretic interpretation of consensus problems as mechanism design problems. Under this perspective a supervisor entails the agents to reach a consensus by imposing individual objectives. We prove that such objectives can be chosen so that rational agents have a unique optimal proto…

Mathematical optimizationMechanism designDynamic agentsComputer sciencemedia_common.quotation_subjectDistributed computingmechanismcontainment controlRational agentStationary consensus protocolsNetwork topologyTopologyUniform consensusComputer Science::Multiagent SystemsSwitching topologiesComputer Science::Systems and ControlDynamic agents; Protocol design; Stationary consensus protocols; Switching topologiesSettore MAT/09 - Ricerca OperativaFunction (engineering)Protocol designProtocol (object-oriented programming)Game theoryMulti agent systemsmedia_common
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Dealing with uncertainty in consensus protocol

2009

Recent results on Consensus protocols for networks are presented. The basic tools and the main contribution available in the literature are considered, together with some of the related challenging aspects: estimation in networks and how to deal with disturbances is considered. Motivated by applications to sensor, peer-to-peer, and ad hoc networks, many papers have considered the problem of estimation in a consensus fashion. Here, the Unknown But Bounded (UBB) noise affecting the network is addressed in details. Because of the presence of UBB disturbances convergence to equilibria with all equal components is, in general, not possible. The solution of the $\epsilon$-consensus problem, where…

Settore ING-INF/04 - AutomaticaConsensus protocol optimizazion disturbancesSettore MAT/09 - Ricerca Operativa
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