Wireless Communications
Geographic gossip: efficient aggregation for sensor networks
Proceedings of the 5th international conference on Information processing in sensor networks
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Distributed Average Consensus using Probabilistic Quantization
SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
Neighborhood gossip: Concurrent averaging through local interference
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
IEEE Transactions on Signal Processing
Broadcast gossip algorithms for consensus
IEEE Transactions on Signal Processing
Greedy gossip with eavesdropping
IEEE Transactions on Signal Processing
Geographic Gossip: Efficient Averaging for Sensor Networks
IEEE Transactions on Signal Processing
Consensus in Ad Hoc WSNs With Noisy Links—Part I: Distributed Estimation of Deterministic Signals
IEEE Transactions on Signal Processing
Distributed Average Consensus With Dithered Quantization
IEEE Transactions on Signal Processing - Part I
Randomized consensus algorithms over large scale networks
IEEE Journal on Selected Areas in Communications
Think globally, act locally: on the reshaping of information landscapes
Proceedings of the 12th international conference on Information processing in sensor networks
On the mean square error of randomized averaging algorithms
Automatica (Journal of IFAC)
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Reaching consensus in a network is an important problem in control, estimation, and resource allocation. While many algorithms focus on computing the exact average of the initial values in the network, in some cases it is more important for nodes to reach a consensus quickly. In a distributed system establishing two-way communication may also be difficult or unreliable. In this paper, the effect of the wireless medium on simple consensus protocol is explored. In a wireless environment, a node's transmission is a broadcast to all nodes which can hear it, and due to signal propagation effects, the neighborhood size may change with time. A class of non-sum preserving algorithms involving unidirectional broadcasting is extended to a time-varying connection model. This algorithm converges almost surely and its expected consensus value is the true average. A simple bound is given on the convergence time.