Big data stream mobile computing is proposed as a paradigm that relies on the convergence of broadband Internet mobile networking and real-time mobile cloud computing. It aims at fostering the rise of novel self-configuring integrated computing-communication platforms for enabling in real time the offloading and processing of big data streams acquired by resource-limited mobile/wireless devices. This position article formalizes this paradigm, discusses its most significant application opportunities, and outlines the major challenges in performing real-time energy-efficient management of the distributed resources available at both mobile devices and Internet-connected data centers. The performance analysis of a small-scale prototype is also included in order to provide insight into the energy vs. performance tradeoff that is achievable through the optimized design of the resource management modules. Performance comparisons with some state-of-the-art resource managers corroborate the discussion. Hints for future research directions conclude the article.

Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing. Review, challenges, and a case study / Baccarelli, Enzo; Cordeschi, Nicola; Mei, Alessandro; Panella, Massimo; Shojafar, Mohammad; Stefa, Julinda. - In: IEEE NETWORK. - ISSN 0890-8044. - STAMPA. - 30:2(2016), pp. 54-61. [10.1109/MNET.2016.7437025]

Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing. Review, challenges, and a case study

BACCARELLI, Enzo;CORDESCHI, Nicola;MEI, Alessandro;PANELLA, Massimo;SHOJAFAR, MOHAMMAD;STEFA, JULINDA
2016

Abstract

Big data stream mobile computing is proposed as a paradigm that relies on the convergence of broadband Internet mobile networking and real-time mobile cloud computing. It aims at fostering the rise of novel self-configuring integrated computing-communication platforms for enabling in real time the offloading and processing of big data streams acquired by resource-limited mobile/wireless devices. This position article formalizes this paradigm, discusses its most significant application opportunities, and outlines the major challenges in performing real-time energy-efficient management of the distributed resources available at both mobile devices and Internet-connected data centers. The performance analysis of a small-scale prototype is also included in order to provide insight into the energy vs. performance tradeoff that is achievable through the optimized design of the resource management modules. Performance comparisons with some state-of-the-art resource managers corroborate the discussion. Hints for future research directions conclude the article.
2016
Data communication systems; data handling; distributed computer systems; energy efficiency; information management; internet; mobile cloud computing; mobile computing; mobile devices
01 Pubblicazione su rivista::01a Articolo in rivista
Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing. Review, challenges, and a case study / Baccarelli, Enzo; Cordeschi, Nicola; Mei, Alessandro; Panella, Massimo; Shojafar, Mohammad; Stefa, Julinda. - In: IEEE NETWORK. - ISSN 0890-8044. - STAMPA. - 30:2(2016), pp. 54-61. [10.1109/MNET.2016.7437025]
File allegati a questo prodotto
File Dimensione Formato  
Baccarelli_Energy-efficient_2016.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 325.14 kB
Formato Adobe PDF
325.14 kB Adobe PDF   Contatta l'autore
Dichiarazione_conformità 18-11-2016.pdf

solo gestori archivio

Tipologia: Altro materiale allegato
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.98 MB
Formato Adobe PDF
1.98 MB Adobe PDF   Contatta l'autore

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/11573/866683
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 185
  • ???jsp.display-item.citation.isi??? 149
social impact