Optimization and Analysis of Distributed Averaging With Short Node Memory

@article{Oreshkin2010OptimizationAA,
  title={Optimization and Analysis of Distributed Averaging With Short Node Memory},
  author={Boris N. Oreshkin and M. Coates and M. Rabbat},
  journal={IEEE Transactions on Signal Processing},
  year={2010},
  volume={58},
  pages={2850-2865}
}
Distributed averaging describes a class of network algorithms for the decentralized computation of aggregate statistics. Initially, each node has a scalar data value, and the goal is to compute the average of these values at every node (the so-called average consensus problem). Nodes iteratively exchange information with their neighbors and perform local updates until the value at every node converges to the initial network average. Much previous work has focused on algorithms where each node… Expand
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