Mobile Cloud Computing Environment as a Support for Mobile Learning

被引:0
|
作者
Kitanov, Stojan [1 ]
Davcev, Danco [1 ]
机构
[1] UIST St Paul Apostle, Ohrid, Macedonia
来源
THIRD INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, GRIDS, AND VIRTUALIZATION (CLOUD COMPUTING 2012) | 2012年
关键词
Cloud Computing (CC); Distance Learning (DL); Mobile Cloud Computing (MCC); Mobile Distance Learning (MDL); High Performance Computing (HPC) Cluster;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper presents a new model of mobile distance learning system (MDL) in an extended mobile cloud computing environment (MCC) by using High Performance Computing (HPC) Cluster Infrastructure, as well as some existing videoconferencing technologies enriched with mobile and wireless devices. This MCC model can be applied everywhere where there is need of fast and intensive computing and analysis of huge amount of data, such as modeling of 3D graphics visualization and animation in ecology, global climate solutions, financial risks, healthcare and medical learning, decoding genome projects, etc. After the MCC model presentation, the experimental system architecture will be provided, as well as its possibilities, with particular reference to mobile learning environment and its potential issues. In this architecture the mobile device may optionally use the open source e-learning course management system platform Moodle, to access the learning material and the relevant data that needs to be transferred to the HPC Cluster Infrastructure for further computing. In order to provide higher quality of presenting the learning material, the Cisco WebEx application will be used to test the distance learning in both fixed and mobile environment. Then, a Quality of Experience (QoE) evaluation of such mobile distance learning system will be provided. Finally, it will be concluded that this MCC model that incorporates HPC Cluster Infrastructure can be applied anywhere where there is need of fast and intensive computing and analysis of huge amount of data which cannot be performed by a conventional PC, Laptop or Mobile Device.
引用
收藏
页码:99 / 105
页数:7
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