Topic
Distributed algorithm
About: Distributed algorithm is a research topic. Over the lifetime, 20416 publications have been published within this topic receiving 548109 citations.
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TL;DR: A fully distributed control strategy based on the consensus algorithm for the optimal resource management in an islanded microgrid is proposed through a multiagent system framework, which only requires information exchange among neighboring agents through a local network.
Abstract: A microgrid is a promising approach to provide clean, renewable, and reliable electricity by integrating various distributed generations and energy storage systems into power systems. However, highly intermittent renewable generations and various load demands pose new challenges to the optimal resource management in a microgrid. This paper proposes a fully distributed control strategy based on the consensus algorithm for the optimal resource management in an islanded microgrid. The proposed strategy is implemented through a multiagent system framework, which only requires information exchange among neighboring agents through a local network. The objective is achieved through a two-level control strategy. The upper control level is a consensus-based optimization algorithm that discovers the reference of optimal power generation or demand while maintaining the supply–demand balance. The lower control level is responsible for reference tracking of the associated component. Simulation results in the IEEE 14- and 162-bus systems are presented to demonstrate the effectiveness of the proposed control strategy.
251 citations
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TL;DR: The verification problem in distributed networks is studied, stated as follows: let H be a subgraph of a network G where each vertex of G knows which edges incident on it are in H.
Abstract: We study the verification problem in distributed networks, stated as follows. Let $H$ be a subgraph of a network $G$ where each vertex of $G$ knows which edges incident on it are in $H$. We would l...
251 citations
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18 Jun 1995TL;DR: In this article, an asynchronous distributed algorithm for optimal rate calculation across the network, where optimality is understood in the maxmin sense, is presented, which quickly converges to the optimal rates and is shown to be well-behaved in transience.
Abstract: As the speed and the dynamic range of computer networks evolve, the issue of efficient traffic management becomes increasingly important. The paper describes an approach to traffic management using explicit rate information provided to the source by the network. The authors present an asynchronous distributed algorithm for optimal rate calculation across the network, where optimality is understood in the maxmin sense. The algorithm quickly converges to the optimal rates and is shown to be well-behaved in transience.
250 citations
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22 Jan 2006TL;DR: This paper provides an almost tight classification of the possible trade-off between the amount of local information and the quality of the global solution for general covering and packing problems and gives a distributed algorithm using only small messages which obtains an (ρΔ)1/k-approximation in time O(k2).
Abstract: Achieving a global goal based on local information is challenging, especially in complex and large-scale networks such as the Internet or even the human brain. In this paper, we provide an almost tight classification of the possible trade-off between the amount of local information and the quality of the global solution for general covering and packing problems. Specifically, we give a distributed algorithm using only small messages which obtains an (ρΔ)1/k-approximation for general covering and packing problems in time O(k2), where ρ depends on the LP's coefficients. If message size is unbounded, we present a second algorithm that achieves an O(n1/k) approximation in O(k) rounds. Finally, we prove that these algorithms are close to optimal by giving a lower bound on the approximability of packing problems given that each node has to base its decision on information from its k-neighborhood.
250 citations
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TL;DR: A distributed leader-follower flocking algorithm for multi-agent dynamical systems with time-varying velocities is developed where each agent is governed by second-order dynamics.
250 citations