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A Framework for Modeling Automatic Offloading of Mobile Applications Using Genetic Programming

  • Gianluigi Folino
  • Francesco Sergio Pisani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7835)

Abstract

The limited battery life of the modern mobile devices is one of the key problems limiting their usage. The offloading of computation on cloud computing platforms can considerably extend the battery duration. However, it is really hard not only to evaluate the cases in which the offloading guarantees real advantages on the basis of the requirements of application in terms of data transfer, computing power needed, etc., but also to evaluate if user requirements (i.e. the costs of using the clouds, a determined QoS required, etc.) are satisfied. To this aim, in this work it is presented a framework for generating models for taking 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. Finally, the fitness function adopted permits to give different weights to the four categories considered during the process of building the model.

Keywords

Mobile Device Cloud Computing Mobile Application User Requirement Inference Engine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gianluigi Folino
    • 1
  • Francesco Sergio Pisani
    • 1
  1. 1.Institute of High Performance Computing and Networking (ICAR-CNR)Italy

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