Abstract
Mobile cloud computing is a promising approach to overcome limitations of mobile devices in terms of battery consumption and capability to execute computation-intensive applications. It consists in outsourcing some parts of computation-intensive applications to cloud servers, so that the overall energy consumption and execution time of application's running are optimized. In addition to classical public/private clouds, computations can also be offloaded to nearby clouds, called cloudlets, which may have different access delays, proximity to end users, computation capability and/or monetary cost. In such a heterogeneous context, the offloading decision becomes very complicated and time-consuming, especially when the number of surrogate sites and application units increase. In this paper, we propose a multisite offloading solution which uses the genetic algorithm to timely achieve the best-possible offloading outcome in a heterogeneous multisite context. Simulation results demonstrated that our proposal can outperform other existing multisite alternatives for different number of surrogate sites and various application sizes.
Original language | English |
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Title of host publication | 2016 8th International Symposium on Telecommunications, IST 2016 |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 660-665 |
Number of pages | 6 |
ISBN (Electronic) | 9781509034345 |
DOIs | |
Publication status | Published - 2017 |
Externally published | Yes |
Event | International Symposium on Telecommunications 2016 - Tehran, Iran Duration: 27 Sept 2016 → 29 Sept 2016 Conference number: 8th https://ieeexplore.ieee.org/xpl/conhome/7878240/proceeding |
Conference
Conference | International Symposium on Telecommunications 2016 |
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Abbreviated title | IST 2016 |
Country/Territory | Iran |
City | Tehran |
Period | 27/09/16 → 29/09/16 |
Internet address |
Keywords
- Computation Offloading
- Mobile Cloud Computing
- Multisite
- Near Optimal Partitioning