Journal article
Optimal scheduling for data transmission between mobile devices and cloud
Information sciences, v 301, pp 169-180
20 Apr 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Mobile cloud computing has emerged as a new computing paradigm promising to extend the capabilities of resource-constrained mobile devices. In this new paradigm, mobile devices are enabled to offload computing tasks, report sensing records, and store large files on the cloud through wireless networks. Therefore, efficient data transmission has become an important issue affecting user experiences on mobile cloud. Considering the limited battery energy of mobile devices and different application requirements on transmission delay, this study presents an online control algorithm (OPERA) based on the Lyapunov optimization theory for optimally scheduling data transmission between mobile devices and cloud. The OPERA algorithm is able to make control decisions on application scheduling, interface selection and packet dropping to minimize a joint utility of network energy cost and packet dropping penalty, without requiring any statistical information of traffic arrivals and link throughputs. Rigorous analysis and extensive simulations have demonstrated its distinguished performance in terms of utility optimality, system stability and service delay.
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Details
- Title
- Optimal scheduling for data transmission between mobile devices and cloud
- Creators
- Weiwei Fang - Beijing Jiaotong UniversityXiaoyan Yin - School of Information Science and Technology, Northwest University, Xi’an 710127, ChinaYuan An - State Key Lab of Astronautical Dynamics of China, Xi’an 710043, ChinaNaixue Xiong - School of Computer Science, Colorado Technical University, Colorado Springs, CO 80907, USAQiwang Guo - State Key Lab of Astronautical Dynamics of China, Xi’an 710043, ChinaJing Li - State Key Lab of Astronautical Dynamics of China, Xi’an 710043, China
- Publication Details
- Information sciences, v 301, pp 169-180
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000350929100011
- Scopus ID
- 2-s2.0-84922721979
- Other Identifier
- 991020547664804721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Information Systems