A lower bound for distributed averaging algorithms on the line graph
Author(s)Tsitsiklis, John N.; Olshevsky, Alexander
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We derive lower bounds on the convergence speed of a widely used class of distributed averaging algorithms. In particular, we prove that any distributed averaging algorithm whose state consists of a single real number and whose (possibly nonlinear) update function satisfies a natural smoothness condition has a worst case running time of at least on the order of n[superscript 2] on a line network of n nodes. Our results suggest that increased memory or expansion of the state space is crucial for improving the running times of distributed averaging algorithms.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the 49th IEEE Conference on Decision and Control (CDC), 2010
Institute of Electrical and Electronics Engineers (IEEE)
Tsitsiklis, John N. and Alexander Olshevsky. "A lower bound for distributed averaging algorithms on the line graph." Proceedings of the 2010 IEEE Conference on Decision and Control (CDC): 4523-4528. © 2010 IEEE.
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