Resource allocation in sparse graphs

K. Y. Michael Wong; David Saad; Zhuo Gao

Resource allocation in sparse graphs

K. Y. Michael Wong, David Saad, Zhuo Gao

Research output: Unpublished contribution to conference › Unpublished Conference Paper › peer-review

Abstract

Resource allocation in sparsely connected networks, a representative problem of systems with real variables, is studied using the replica and Bethe approximation methods. An efficient distributed algorithm is devised on the basis of insights gained from the analysis and is examined using numerical simulations,showing excellent performance and full agreement with the theoretical results. The physical properties of the resource allocation model are discussed.

Original language	English
Publication status	Published - 14 Nov 2005
Event	European Conference on Complex Systems, 2005 - Paris, France Duration: 1 Jan 2005 → 1 Jan 2005

Conference

Conference	European Conference on Complex Systems, 2005
Country/Territory	France
City	Paris
Period	1/01/05 → 1/01/05

Bibliographical note

Licensed under a Creative Commons Attribution 2.5 License http://creativecommons.org/licenses/by-sa/2.5/

Keywords

Statistical physics
inference
message passing
resource allocation
sparse graphs

Access to Document

NCRG_2005_006.pdf
Licensed under a Creative Commons Attribution 2.5 License http://creativecommons.org/licenses/by-sa/2.5/
Accepted author manuscript, 54.6 KB

Cite this

@conference{e6a32c1d39d14c9da281d5b91a8aec4b,

title = "Resource allocation in sparse graphs",

abstract = "Resource allocation in sparsely connected networks, a representative problem of systems with real variables, is studied using the replica and Bethe approximation methods. An efficient distributed algorithm is devised on the basis of insights gained from the analysis and is examined using numerical simulations,showing excellent performance and full agreement with the theoretical results. The physical properties of the resource allocation model are discussed.",

keywords = "Statistical physics, inference, message passing, resource allocation, sparse graphs",

author = "Wong, {K. Y. Michael} and David Saad and Zhuo Gao",

note = "Licensed under a Creative Commons Attribution 2.5 License http://creativecommons.org/licenses/by-sa/2.5/; European Conference on Complex Systems, 2005 ; Conference date: 01-01-2005 Through 01-01-2005",

year = "2005",

month = nov,

day = "14",

language = "English",

}

TY - CONF

T1 - Resource allocation in sparse graphs

AU - Wong, K. Y. Michael

AU - Saad, David

AU - Gao, Zhuo

N1 - Licensed under a Creative Commons Attribution 2.5 License http://creativecommons.org/licenses/by-sa/2.5/

PY - 2005/11/14

Y1 - 2005/11/14

N2 - Resource allocation in sparsely connected networks, a representative problem of systems with real variables, is studied using the replica and Bethe approximation methods. An efficient distributed algorithm is devised on the basis of insights gained from the analysis and is examined using numerical simulations,showing excellent performance and full agreement with the theoretical results. The physical properties of the resource allocation model are discussed.

AB - Resource allocation in sparsely connected networks, a representative problem of systems with real variables, is studied using the replica and Bethe approximation methods. An efficient distributed algorithm is devised on the basis of insights gained from the analysis and is examined using numerical simulations,showing excellent performance and full agreement with the theoretical results. The physical properties of the resource allocation model are discussed.

KW - Statistical physics

KW - inference

KW - message passing

KW - resource allocation

KW - sparse graphs

UR - http://complexite.free.fr/ECCS/

M3 - Unpublished Conference Paper

T2 - European Conference on Complex Systems, 2005

Y2 - 1 January 2005 through 1 January 2005

ER -

Resource allocation in sparse graphs

Abstract

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this