Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments

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. Resear...

Full description

Bibliographic Details
Main Authors: Jose M. Moya, José L. Risco-Martín, Jose L. Ayala, Cesar Sanchez, Marina Zapater
Format: Article
Language:English
Published: MDPI AG 2012-08-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/12/8/10659
id doaj-424226b3b6784a3e95784a08a48c3bc6
record_format Article
spelling doaj-424226b3b6784a3e95784a08a48c3bc62020-11-25T01:05:28ZengMDPI AGSensors1424-82202012-08-01128106591067710.3390/s120810659Ubiquitous Green Computing Techniques for High Demand Applications in Smart EnvironmentsJose M. MoyaJosé L. Risco-MartínJose L. AyalaCesar SanchezMarina ZapaterUbiquitous 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.http://www.mdpi.com/1424-8220/12/8/10659ubiquitous sensor networkgreen computingheterogeneous systemsdata centershigh performance computingsmart citiesambient intelligence
collection DOAJ
language English
format Article
sources DOAJ
author Jose M. Moya
José L. Risco-Martín
Jose L. Ayala
Cesar Sanchez
Marina Zapater
spellingShingle Jose M. Moya
José L. Risco-Martín
Jose L. Ayala
Cesar Sanchez
Marina Zapater
Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments
Sensors
ubiquitous sensor network
green computing
heterogeneous systems
data centers
high performance computing
smart cities
ambient intelligence
author_facet Jose M. Moya
José L. Risco-Martín
Jose L. Ayala
Cesar Sanchez
Marina Zapater
author_sort Jose M. Moya
title Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments
title_short Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments
title_full Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments
title_fullStr Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments
title_full_unstemmed Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments
title_sort ubiquitous green computing techniques for high demand applications in smart environments
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2012-08-01
description 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.
topic ubiquitous sensor network
green computing
heterogeneous systems
data centers
high performance computing
smart cities
ambient intelligence
url http://www.mdpi.com/1424-8220/12/8/10659
work_keys_str_mv AT josemmoya ubiquitousgreencomputingtechniquesforhighdemandapplicationsinsmartenvironments
AT joselriscomartin ubiquitousgreencomputingtechniquesforhighdemandapplicationsinsmartenvironments
AT joselayala ubiquitousgreencomputingtechniquesforhighdemandapplicationsinsmartenvironments
AT cesarsanchez ubiquitousgreencomputingtechniquesforhighdemandapplicationsinsmartenvironments
AT marinazapater ubiquitousgreencomputingtechniquesforhighdemandapplicationsinsmartenvironments
_version_ 1725194314206674944