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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22 Apr 2003
TL;DR: A distributed algorithm for environmental monitoring of a scalar field (such as temperature, intensity of light, atmospheric pressure, etc.) using a random sensor network is presented.
Abstract: We present a distributed algorithm for environmental monitoring of a scalar field (such as temperature, intensity of light, atmospheric pressure, etc.) using a random sensor network.We derive an error estimate, discuss the average complexity of the algorithm, and present some simulation results.
131 citations
TL;DR: This work considers the development of single-timescale schemes for the distributed computation of equilibria associated with Nash games in which each player solves a convex program, a class of games that lead to monotone variational inequalities.
Abstract: We consider the development of single-timescale schemes for the distributed computation of equilibria associated with Nash games in which each player solves a convex program. Equilibria associated with such games are wholly captured by the solution set of a variational inequality. Our focus is on a class of games, termed monotone Nash games, that lead to monotone variational inequalities. Distributed extensions of standard approaches for solving such variational problems are characterized by two challenges: (1) Unless suitable assumptions (such as strong monotonicity) are imposed on the mapping arising in the specification of the variational inequality, iterative methods often require the solution of a sequence of regularized problems, a naturally two-timescale process that is harder to implement in practice. (2) Additionally, algorithm parameters for all players (such as steplengths and regularization parameters) have to be chosen centrally and communicated to all players; importantly, these parameters c...
131 citations
TL;DR: Simulation results show the effectiveness and performance of the proposed continuous-time algorithms and show that the convergence rate of second-order algorithm is faster than that of first-order distributed algorithm.
Abstract: This paper proposes two second-order continuous-time algorithms to solve the economic power dispatch problem in smart grids. The collective aim is to minimize a sum of generation cost function subject to the power demand and individual generator constraints. First, in the framework of nonsmooth analysis and algebraic graph theory, one distributed second-order algorithm is developed and guaranteed to find an optimal solution. As a result, the power demand constraints can be kept all the time under appropriate initial condition. The second algorithm is under a centralized framework, and the optimal solution is robust in the sense that different initial power conditions do not change the convergence of the optimal solution. Finally, simulation results based on five-unit system, IEEE 30-bus system, and IEEE 300-bus system show the effectiveness and performance of the proposed continuous-time algorithms. The examples also show that the convergence rate of second-order algorithm is faster than that of first-order distributed algorithm.
131 citations
TL;DR: Two new distributed scheduling policies for ad hoc wireless networks that can achieve provable capacity regions are proposed that are constant-time policies, i.e., the time needed for computing a schedule is independent of the network size.
Abstract: We propose a new class of distributed scheduling policies for ad hoc wireless networks that can achieve provable capacity regions. Previously known scheduling policies that guarantee comparable capacity regions are either centralized or require computation time that increases with the size of the network. In contrast, the unique feature of the proposed distributed scheduling policies is that they are constant-time policies, i.e., given a fixed approximation ratio and a bounded maximum node-degree of the network, the time needed for computing a new schedule is independent of the network size. Hence, they can be easily deployed in large networks.
131 citations
24 Mar 2004
TL;DR: This work proposes sFlow, a fully distributed algorithm to be executed on all service nodes, such that the federated service flow graph is resource efficient, performs well, and meets the demands of service consumers.
Abstract: Existing research work towards the composition of complex federated services has assumed that service requests and deliveries flow through a particular service path or tree. Here, we extend such a service model to a directed acyclic graph, allowing services to be delivered via parallel paths and interleaved with each other. Such an assumption of the service flow model has apparently introduced complexities towards the development of a distributed algorithm to federate existing services, as well as the provisioning of the required quality in the most resource-efficient fashion. To this end, we propose sFlow, a fully distributed algorithm to be executed on all service nodes, such that the federated service flow graph is resource efficient, performs well, and meets the demands of service consumers.
131 citations