Treffer: Optimal Topology Control and Power Allocation for Minimum Energy Consumption in Consensus Networks

Title:
Optimal Topology Control and Power Allocation for Minimum Energy Consumption in Consensus Networks
Authors:
SARDELLITTI, Stefania, BARBAROSSA, Sergio, SWAMI, Ananthram
Source:
IEEE transactions on signal processing. 60(1):383-399
Publisher Information:
New York, NY: Institute of Electrical and Electronics Engineers, 2012.
Publication Year:
2012
Physical Description:
print, 28 ref
Original Material:
INIST-CNRS
Subject Terms:
Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Signal, bruit, Signal, noise, Détection, estimation, filtrage, égalisation, prédiction, Detection, estimation, filtering, equalization, prediction, Algorithme, Algorithm, Algoritmo, Allocation puissance, Power allocation, Asignación potencia, Architecture réseau, Network architecture, Arquitectura red, Capteur mesure, Measurement sensor, Captador medida, Commande optimale, Optimal control, Control óptimo, Comportement asymptotique, Asymptotic behavior, Comportamiento asintótico, Consommation électricité, Electric power consumption, Consumo electricidad, Détection signal, Signal detection, Detección señal, Energie minimale, Minimum energy, Energía mínima, Graphe aléatoire, Random graph, Grafo aleatorio, Implémentation, Implementation, Implementación, Modèle déterministe, Deterministic model, Modelo determinista, Méthode combinatoire, Combinatorial method, Método combinatorio, Méthode itérative, Iterative method, Método iterativo, Optimisation, Optimization, Optimización, Performance algorithme, Algorithm performance, Resultado algoritmo, Précision, Accuracy, Precisión, Réseau capteur, Sensor array, Red sensores, Réseau sans fil, Wireless network, Red sin hilo, Structure topologique, Topological structure, Estructura topológica, Traitement signal, Signal processing, Procesamiento señal, Télécommunication sans fil, Wireless telecommunication, Telecomunicación sin hilo, Télédétection, Remote sensing, Teledetección, Valeur propre, Eigenvalue, Valor propio, Consensus algorithms, minimum energy consumption, random graphs, sensor networks, topology control
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
DIET, Sapienza University of Rome, 00184 Rome, Italy
ARL, Adelphi, MD 20783, United States
ISSN:
1053-587X
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=25512508
Rights:
Copyright 2015 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:
Telecommunications and information theory
Accession Number:
edscal.25512508
Database:
PASCAL Archive

Weitere Informationen

Consensus algorithms have generated a lot of interest due to their ability to compute globally relevant statistics by only exploiting local communications among sensors. However, when implemented over wireless sensor networks, the inherent iterative nature of consensus algorithms may cause a large energy consumption. Hence, to make consensus algorithms really appealing in sensor networks, it is necessary to minimize the energy necessary to reach a consensus, within a given accuracy. We propose a method to optimize the network topology and the power allocation over each active link in order to minimize the energy consumption. We consider two network models: a deterministic model, where the nodes are located arbitrarily but their positions are known, and a random model, where the network topology is modeled as a random geometric graph (RGG). In the first case, we show how to convert the topology optimization problem, which is inherently combinatorial, into a parametric convex problem, solvable with efficient algorithms. In the second case, we optimize the power transmitted by each node, exploiting the asymptotic distributions of the eigenvalues of the adjacency matrix of an RGG. We further show that the optimal power can be found as the solution of a convex problem. The theoretical findings are corroborated with extensive simulation results.