Joint resource allocation and offloading strategies in cloud enabled cellular networks
- 1 June 2015
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 5529-5534
- https://doi.org/10.1109/icc.2015.7249203
Abstract
The numerous features installed in recent mobile phones opened the door to a wide range of applications involving localization, storage, photo and video taking and communication. A significant number of applications involve user generated content and require intensive processing which limits dramatically the battery lifetime of featured mobile terminals. Mobile cloud computing has been recently proposed as a promising solution allowing the mobile users to run computing-intensive and energy parsimonious applications. This new feature requires new functionalities inside the cellular network architecture and needs appropriate resource allocation strategies which account for computation and communication in the same time. In this paper we present promising options to upgrade 4G architecture to support these new features. We also present two resource allocation strategies accounting for both computation and radio resources. These strategies are devised so that to minimize the energy consumption of the mobile terminals while satisfying predefined delay constraints. We compare online learning based solutions where the network adapts dynamically to the application that is run on mobile terminals, and pre-calculated offline solutions which are employed when a certain level of knowledge about the application and the channel conditions is available at the network side. We show, that even with imperfect knowledge about the application, pre-calculated offline strategies offer better performance in terms of energy consumption of mobile terminals.Keywords
This publication has 10 references indexed in Scilit:
- Joint allocation of computation and communication resources in multiuser mobile cloud computingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Efficient Resource Provisioning and Rate Selection for Stream Mining in a Community CloudIEEE Transactions on Multimedia, 2013
- Data offloading techniques in 3GPP Rel-10 networks: A tutorialIEEE Communications Magazine, 2012
- A Dynamic Offloading Algorithm for Mobile ComputingIEEE Transactions on Wireless Communications, 2012
- ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloadingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clonesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- NAOPublished by Association for Computing Machinery (ACM) ,2011
- Cloud Computing for Mobile Users: Can Offloading Computation Save Energy?Computer, 2010
- What's inside the Cloud? An architectural map of the Cloud landscapePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- An on-line learning algorithm for energy efficient delay constrained scheduling over a fading channelIEEE Journal on Selected Areas in Communications, 2008