An anytime distributed load balancing algorithm satisfying capacity and quantization constraints

Evan Gravelle and Sonia Martínez
IEEE Transactions on Control of Network Systems, 4 (2) (2018) 583-609

Abstract:

Current research in the field of distributed consensus algorithms fails to adequately address physical limitations of real systems. This paper proposes a new algorithm for quantized distributed load balancing over a network of agents subject to upper-limit constraints. More precisely, loads are integer values, and nodes are constrained to remain under maximum load capacities at all times. Convergence to a set of desired states is proven for all connected graphs and any feasible initial load distribution, provided that nodes with small maximum capacities have a 2-hop separation condition and have at least two neighbors. We present simulations that verify our results and discuss possible extensions of the algorithm.

File: Extended version

Bib-tex entry:

@article{EG-SM:18-tcns,
author = {E. Gravelle and S. Mart{\'\i}nez},
title = {An anytime distributed load balancing algorithm satisfying capacity and quantization constraints},
journal= {IEEE Transactions on Control of Network Systems},
year = {2018},
volume = {4},
number = {2},
pages = {583--609}
}