@inproceedings{1e20da7591e54f90b68e39027a1bdad5,
title = "Online algorithms for location-aware task offloading in two-tiered mobile cloud environments",
abstract = "Mobile Cloud Computing (MCC) is emerging as a main ubiquitous computing platform which enables to leverage the resource limitations of mobile devices and wireless networks by offloading data-intensive computation tasks from resource-poor mobile devices to resource-rich clouds. In this paper, we consider an online location-aware offloading problem in a two-tiered mobile cloud computing environment consisting of a local cloudlet and remote clouds, with an objective to fair share the use of the cloudlet by consuming the same proportional of their mobile device energy, while keeping their individual SLA, for which we devise an efficient online algorithm. We also conduct experiments by simulations to evaluate the performance of the proposed algorithm. Experimental results demonstrate that the proposed algorithm is promising and outperforms other heuristics.",
keywords = "Energy optimization, Location-aware application, Maximum matching, Multi-tired mobile computing, Online offloading algorithms",
author = "Qiufen Xia and Weifa Liang and Zichuan Xu and Bingbing Zhou",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 7th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2014 ; Conference date: 08-12-2014 Through 11-12-2014",
year = "2014",
month = jan,
day = "29",
doi = "10.1109/UCC.2014.19",
language = "English",
series = "Proceedings - 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing, UCC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "109--116",
booktitle = "Proceedings - 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing, UCC 2014",
address = "United States",
}