Automatic offloading of mobile applications into the cloud by means of genetic programming (Articolo in rivista)

Type
Label
  • Automatic offloading of mobile applications into the cloud by means of genetic programming (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1016/j.asoc.2014.09.016 (literal)
Alternative label
  • Folino, Gianluigi; Pisani, Francesco Sergio (2014)
    Automatic offloading of mobile applications into the cloud by means of genetic programming
    in Applied soft computing (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Folino, Gianluigi; Pisani, Francesco Sergio (literal)
Pagina inizio
  • 253 (literal)
Pagina fine
  • 265 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.scopus.com/record/display.url?eid=2-s2.0-84908119103&origin=inward (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 25 (literal)
Rivista
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto Di Calcolo E Reti Ad Alte Prestazioni, Rende (literal)
Titolo
  • Automatic offloading of mobile applications into the cloud by means of genetic programming (literal)
Abstract
  • The limited battery life of modern mobile devices is one of the key problems limiting their use. Even if the offloading of computation onto cloud computing platforms can considerably extend battery duration, it is really hard not only to evaluate the cases where offloading guarantees real advantages on the basis of the requirements of the application in terms of data transfer, computing power needed, etc., but also to evaluate whether user requirements (i.e. the costs of using the cloud services, a determined QoS required, etc.) are satisfied. To this aim, this paper presents a framework for generating models to make automatic decisions on the offloading of mobile applications using a genetic programming (GP) approach. The GP system is designed using a taxonomy of the properties useful to the offloading process concerning the user, the network, the data and the application. The fitness function adopted permits different weights to be given to the four categories considered during the process of building the model. Experimental results, conducted on datasets representing different categories of mobile applications, permit the analysis of the behavior of our algorithm in different applicative contexts. Finally, a comparison with the state of the art of the classification algorithm establishes the goodness of the approach in modeling the offloading process. (literal)
Prodotto di
Autore CNR
Insieme di parole chiave

Incoming links:


Prodotto
Autore CNR di
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi
Insieme di parole chiave di
data.CNR.it