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In this paper, we propose a new decentralized algorithm to solve the consensus on the average problem on sensor networks through a gossip algorithm based on broadcasts. We directly extend previous results by not requiring that the digraph representing the network topology be balanced. Our algorithm is an improvement with respect to known gossip algorithms based on broadcasts in that the average of...
In this paper we study the problem of fault diagnosis for sensor networks.We examine faults that involve an anomalous behavior of the sensor and investigate their diagnosis only through the local interaction between faulty nodes and healthy ones. We provide heuristics to actively diagnose faults and recover the nominal behavior.
The main contribution of this paper is an algorithm to solve the quantized consensus problem over networks represented by Hamiltonian graphs, i.e., graphs containing a Hamiltonian cycle. The algorithm is proved to converge almost surely to a finite set containing the optimal solution. A worst case study of the average convergence time is carried out, thus proving the efficiency of the algorithm with...
In this paper we consider the problem of load balancing over heterogeneous networks, i.e. networks whose nodes have different speeds. We assume that tasks are indivisible and with different weights. Our goal is that of minimizing the maximum execution time over nodes. We provide a gossip-based distributed algorithm whose convergence to a bounded set is guaranteed. We show that the convergence time...
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