visual sensor network (VSN) consists of a large amount of camera nodes which are able to process the captured image data locally and to extract the relevant information. The tight resource limitations in these networks of embedded sensors and processors represent a major challenge for the application development. In this paper we focus on finding optimal VSN configurations which are basically given by (i) the selection of cameras to sufficiently monitor the area of interest, (ii) the setting of the cameras’ frame rate and resolution to fulfill the quality of service (QoS) requirements, and (iii) the assignment of processing tasks to cameras to achieve all required monitoring activities. We formally specify this configuration problem and describe an efficient approximation method based on an evolutionary algorithm. We analyze our approximation method on three different scenarios and compare the predicted results with measurements on real implementations on a VSN platform. We finally combine our approximation method with an expectation-maximization algorithm for optimizing the coverage and resource allocation in VSN with pan-tilt-zoom (PTZ) camera nodes.

Resource-Aware Coverage and Task Assignment in Visual Sensor Networks

MICHELONI, Christian;
2011-01-01

Abstract

visual sensor network (VSN) consists of a large amount of camera nodes which are able to process the captured image data locally and to extract the relevant information. The tight resource limitations in these networks of embedded sensors and processors represent a major challenge for the application development. In this paper we focus on finding optimal VSN configurations which are basically given by (i) the selection of cameras to sufficiently monitor the area of interest, (ii) the setting of the cameras’ frame rate and resolution to fulfill the quality of service (QoS) requirements, and (iii) the assignment of processing tasks to cameras to achieve all required monitoring activities. We formally specify this configuration problem and describe an efficient approximation method based on an evolutionary algorithm. We analyze our approximation method on three different scenarios and compare the predicted results with measurements on real implementations on a VSN platform. We finally combine our approximation method with an expectation-maximization algorithm for optimizing the coverage and resource allocation in VSN with pan-tilt-zoom (PTZ) camera nodes.
File in questo prodotto:
File Dimensione Formato  
Resource-Aware Coverage and Task Assignment in Visual Sensor Networks.pdf

non disponibili

Tipologia: Altro materiale allegato
Licenza: Non pubblico
Dimensione 1.17 MB
Formato Adobe PDF
1.17 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/868469
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 80
  • ???jsp.display-item.citation.isi??? 74
social impact