Title :
Quantized distributed load balancing with capacity constraints
Author :
Gravelle, Evan ; Martinez, Sonia
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Univ. of California, San Diego, La Jolla, CA, USA
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, any feasible initial load distribution, and separation and connectivity conditions on nodes with small maximum capacities. Simulations illustrate our results.
Keywords :
distributed algorithms; graph theory; resource allocation; capacity constraints; connected graphs; connectivity condition; distributed consensus algorithms; integer value; load distribution; quantized distributed load balancing; separation condition; upper-limit constraints; Algorithm design and analysis; Approximation algorithms; Convergence; Heuristic algorithms; Load management; Nickel; Program processors;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7039989
