GreenDisc: a HW/SW energy optimization framework in globally distributed computation

Zapater Sancho, Marina; Ayala Rodrigo, José Luis y Moya Fernández, José Manuel (2012). GreenDisc: a HW/SW energy optimization framework in globally distributed computation. "Lecture Notes in Computer Science", v. 7656 ; pp. 1-8. ISSN 0302-9743. https://doi.org/10.1007/978-3-642-35377-2_1.

Descripción

Título: GreenDisc: a HW/SW energy optimization framework in globally distributed computation
Autor/es:
  • Zapater Sancho, Marina
  • Ayala Rodrigo, José Luis
  • Moya Fernández, José Manuel
Tipo de Documento: Artículo
Título de Revista/Publicación: Lecture Notes in Computer Science
Fecha: Diciembre 2012
Volumen: 7656
Materias:
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería Electrónica
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

In recent future, wireless sensor networks (WSNs) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of WSNs facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers (DCs). The high economical and environmental impact of the energy consumption in DCs requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of WSNs: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of DCs: energy-optimal workload assignment policies in heterogeneous DCs, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

Más información

ID de Registro: 16826
Identificador DC: http://oa.upm.es/16826/
Identificador OAI: oai:oa.upm.es:16826
Identificador DOI: 10.1007/978-3-642-35377-2_1
URL Oficial: http://link.springer.com/chapter/10.1007%2F978-3-642-35377-2_1
Depositado por: Memoria Investigacion
Depositado el: 10 Ago 2013 08:27
Ultima Modificación: 21 Abr 2016 17:10
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