Decentralized Aggregation Protocols in Peer-to-Peer Networks: A Survey
MACE '09 Proceedings of the 4th IEEE International Workshop on Modelling Autonomic Communications Environments
Load balancing over heterogeneous networks with gossip-based algorithms
ACC'09 Proceedings of the 2009 conference on American Control Conference
Distributed consensus on camera pose
IEEE Transactions on Image Processing
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This paper investigates the use of spatial gossip to compute the average consensus in networks such as grids or random geometric graphs, where connectivity is a function of proximity. Randomized gossip is a framework for distributed computation where, at each iteration, a random pair of nodes exchanges information, and then updates their local values by averaging. This simple protocol converges to an average consensus: every node obtains the average of the initial values across the network. In spatial gossip, if the distance between two nodes is d, then they communicate with probability proportional to d-β for some β ≥ 0. The special case β = 0 corresponds to an algorithm known in the sensor network literature as geographic gossip. Dimakis et al. have shown that geographic gossip computes the average to accuracy n-1 in O(n3/2√log n) transmissions. In this paper we show that the same rates are achieved for β = 2 and β = 3. Each setting offers a different balance between the rate of convergence (in gossip rounds) and the average number of transmissions per gossip round. We illustrate, via simulation, that spatial gossip with β = 2 generally yields superior performance over geographic gossip by a constant factor.