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

fYear

2014

fDate

15-17 Dec. 2014

Firstpage

3866

Lastpage

3871

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on

Conference_Location

Los Angeles, CA

Print_ISBN

978-1-4799-7746-8

Type

conf

DOI

10.1109/CDC.2014.7039989

Filename

7039989