Result: Networked slepian-wolf: Theory and algorithms

Title:
Networked slepian-wolf: Theory and algorithms
Authors:
CRISTESCU, Razvan, BEFERULL-LOZANO, Baltasar, VETTERLI, Martin
Source:
Wireless sensor networks (Berlin, 19-21 January 2004)Lecture notes in computer science. :44-59
Publisher Information:
Berlin: Springer, 2004.
Publication Year:
2004
Physical Description:
print, 19 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Logiciel, Software, Généralités, General, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Reconnaissance et synthèse de la parole et du son. Linguistique, Speech and sound recognition and synthesis. Linguistics, Allocation optimale, Optimal allocation, Asignación óptima, Collecte donnée, Data gathering, Recolección dato, Consommation énergie, Energy consumption, Consumo energía, Contexte, Context, Contexto, Coût, Costs, Coste, Fonction coût, Cost function, Función coste, Fonction énergie, Energy function, Función energía, Minimisation, Minimization, Minimización, Optimisation, Optimization, Optimización, Problème arbre Steiner, Steiner tree problem, Problema arbol Steiner, Programmation linéaire, Linear programming, Programación lineal, Reconnaissance forme, Pattern recognition, Reconocimiento patrón, Réseau capteur, Sensor array, Red sensores, Solution exacte, Exact solution, Solución exacta, Solution optimale, Optimal solution, Solución óptima, Sous produit, By product, Subproducto, Superposition, Superposición, Théorie algorithme, Algorithm theory, Traitement image, Image processing, Procesamiento imagen, Traitement parole, Speech processing, Tratamiento palabra
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Laboratory for Audio-Visual Communications (LCAV), Swiss Federal Institute of Technology (EPFL), Lausanne 1015, Switzerland
Department of EECS, University of California at Berkeley, Berkeley CA 94720, United States
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=15691156
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.15691156
Database:
PASCAL Archive

Further Information

In this paper, we consider the minimization of a relevant energy consumption related cost function in the context of sensor networks where correlated sources are generated at various sets of source nodes and have to be transmitted to some set of sink nodes. The cost function we consider is given by the product [rate] x [link weight]. The minimization is achieved by jointly optimizing the transmission structure, which we show consists of a superposition of trees from each of the source nodes to its corresponding sink nodes, and the rate allocation across the source nodes. We show that the overall minimization can be achieved in two concatenated steps. First, the optimal transmission structure has to be found, which in general amounts to finding a Steiner tree and second, the optimal rate allocation has to be obtained by solving a linear programming problem with linear cost weights determined by the given optimal transmission structure. We also prove that, if any arbitrary traffic matrix is allowed, then the problem of finding the optimal transmission structure is NP-complete. For some particular traffic matrix cases, we fully characterize the optimal transmission structures and we also provide a closed-form solution for the optimal rate-allocation. Finally, we analyze the design of decentralized algorithms in order to obtain exactly or approximately the optimal rate allocation, depending on the traffic matrix case. For the particular case of data gathering, we provide experimental results showing a good performance in terms of approximation ratios.