Ubiquitous green computing techniques for high demand applications in smart environments

Zapater Sancho, Marina and Sánchez, Cesar and Ayala Rodrigo, José Luis and Moya Fernández, José Manuel and Risco Martín, José Luis (2012). Ubiquitous green computing techniques for high demand applications in smart environments. "Sensors", v. 12 (n. 8); pp. 10659-10677. ISSN 1424-8220. https://doi.org/10.3390/s120810659.

Description

Title: Ubiquitous green computing techniques for high demand applications in smart environments
Author/s:
  • Zapater Sancho, Marina
  • Sánchez, Cesar
  • Ayala Rodrigo, José Luis
  • Moya Fernández, José Manuel
  • Risco Martín, José Luis
Item Type: Article
Título de Revista/Publicación: Sensors
Date: August 2012
ISSN: 1424-8220
Volume: 12
Subjects:
Freetext Keywords: ubiquitous sensor network; green computing; heterogeneous systems; data centers; high performance computing; smart cities; ambient intelligence
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.

More information

Item ID: 16824
DC Identifier: http://oa.upm.es/16824/
OAI Identifier: oai:oa.upm.es:16824
DOI: 10.3390/s120810659
Official URL: http://www.mdpi.com/1424-8220/12/8/10659
Deposited by: Memoria Investigacion
Deposited on: 07 Aug 2013 15:54
Last Modified: 21 Apr 2016 17:10
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