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23
NewtonRaphson consensus for distributed convex optimization
 In CDC and European Control Conference
, 2011
"... Abstract — We study the problem of unconstrained distributed optimization in the context of multiagents systems subject to limited communication connectivity. In particular we focus on the minimization of a sum of convex cost functions, where each component of the global function is available only ..."
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Cited by 21 (9 self)
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Abstract — We study the problem of unconstrained distributed optimization in the context of multiagents systems subject to limited communication connectivity. In particular we focus on the minimization of a sum of convex cost functions, where each component of the global function is available only to a specific agent and can thus be seen as a private local cost. The agents need to cooperate to compute the minimizer of the sum of all costs. We propose a consensuslike strategy to estimate a NewtonRaphson descending update for the local estimates of the global minimizer at each agent. In particular, the algorithm is based on the separation of timescales principle and it is proved to converge to the global minimizer if a specific parameter that tunes the rate of convergence is chosen sufficiently small. We also provide numerical simulations and compare them with alternative distributed optimization strategies like the Alternating Direction Method of Multipliers and the Distributed Subgradient Method. Index Terms — distributed optimization, convex optimization, consensus algorithms, multiagent systems, NewtonRaphson methods I.
Distributed statistical estimation of the number of nodes in sensor networks
 In Conference on Decision and Control (CDC 2010
, 2010
"... Abstract — The distributed estimation of the number of active sensors in a network can be important for estimation and organization purposes. We propose a design methodology based on the following paradigm: some locally randomly generated values are exchanged among the various sensors and thus modi ..."
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Cited by 13 (6 self)
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Abstract — The distributed estimation of the number of active sensors in a network can be important for estimation and organization purposes. We propose a design methodology based on the following paradigm: some locally randomly generated values are exchanged among the various sensors and thus modified by known consensusbased strategies. Statistical analysis of the aconsensus values allows estimation of the number of participant sensors. The main features of this approach are: algorithms are completely distributed, since they do not require leader election steps; sensors are not requested to transmit authenticative information (for example identificative numbers or similar data), and thus the strategy can be implemented whenever privacy problems arise. After a rigorous formulation of the paradigma we analyze some practical examples, fully characterize them from a statistical point of view, and finally we provide some general theoretical results and asymptotic analyses. Index Terms — sensor networks, distributed estimation, number of sensors, consensus algorithms I.
The Wireless Sensor Networks for CityWide Ambient Intelligence (WISEWAI) Project
 Sensors 2009
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Distributed PARAFAC based DSCDMA blind receiver for wireless sensor networks
 In Proc. of the IEEE Workshop SPAWC
, 2010
"... HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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Cited by 6 (3 self)
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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Distributed consensusbased Bayesian estimation: sufficient conditions for performance characterization
 2010 American Control Conference
, 2010
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1 An asynchronous consensusbased algorithm for estimation from noisy relative measurements
"... Abstract—In this work we address the problem of optimal estimating the position of each agent in a network from relative noisy vectorial distances with its neighbors. Although the problem can be cast as a standard leastsquares problem, the main challenge is to devise scalable algorithms that allow ..."
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Abstract—In this work we address the problem of optimal estimating the position of each agent in a network from relative noisy vectorial distances with its neighbors. Although the problem can be cast as a standard leastsquares problem, the main challenge is to devise scalable algorithms that allow each agent to estimate its own position by means of only local communication and bounded complexity, independently of the network size and topology. We propose a consensusbased algorithm with the use of local memory variables which allows asynchronous implementation, has guaranteed exponential convergence to the optimal solution under mild deterministic and randomised communication protocols, and requires minimal packet transmission. In the randomized scenario we then study the rate of convergence in expectation of the estimation error and we argue that it can be used to obtain upper and lower bound for the rate of converge in mean square. In particular, we show that for regular graphs the convergence rate in expectation is reduced by a factor N, which is the number of nodes, which is the same asymptotic degradation of memoryless asynchronous consensus algorithms. Additionally, we show that the asynchronous implementation is also robust to delays and communication failures. We finally complement the analytical results with some numerical simulations comparing the proposed strategy with other algorithms which have been recently proposed in the literature. Index Terms—Wireless sensor networks, distributed localization algorithms, consensus algorithms I.
Almost sure convergence of a randomized algorithm for relative localization in sensor networks
 in Proceedings of the IEEE Conference on Decision and Control
, 2013
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Randomized Gossip Algorithms for Solving Laplacian Systems
"... Abstract—We consider the problem of solving a Laplacian system of equations Lx = b in a distributed fashion, where L is the Laplacian of the communication graph. Solving Laplacian systems arises in a number of applications including consensus, distributed control, clock synchronization, localizat ..."
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Abstract—We consider the problem of solving a Laplacian system of equations Lx = b in a distributed fashion, where L is the Laplacian of the communication graph. Solving Laplacian systems arises in a number of applications including consensus, distributed control, clock synchronization, localization and calculating effective resistances, to name a few. We leverage our analysis on a randomized variant of Kaczmarz’s algorithm to propose a distributed asynchronous gossip algorithm with expected exponential convergence. We quantify the convergence rate depending solely on properties of the network topology, and further propose an accelerated version that scales favorably for larger networks. Our approach naturally extends to leastsquares estimation of general linear systems where each row/column is assigned to nodes of a given network. Last but not least, we show that average consensus is a special case in our framework.