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Guideme: An Optimized Mobile Learning Model Based on Cloud Offloading Computation

Advances in Computer, Communication and Computational Sciences • 2020
العودة
معلومات البحث
المؤلفون Rasha Elstohy, Wael Karam, Nouran Radwan, Eman Monir
الكلمات المفتاحية Mobile learning · Cloud computing · Offloading computation ·Response time
المجلة العلمية Advances in Computer, Communication and Computational Sciences
الناشر © Springer Nature Singapore
المجلد 1158
العدد Not Available
الصفحات Not Available
publication.type International
رابط البحث Open Link
المواد المرفقة Not Available
الملخص
There is growing interest in using mobile learning systems to improve connection between various partners in educational institutions. With mobile learning, there are variety of users, services, education contents, and resources; in any case, how to deploy M-learning applications is quite a challenging demand. On the other side, the addressed success of cloud computing as a large-scale economic paradigm with virtualization appeared to resolve issues as storage capacity, resource pooling, elasticity, and offloading. This research gained benefits from cloud computing resources and capabilities in proposing effective mobile learning model. We specifically address a case study for students and their learners applied on Egyptian schools. Guideme is implemented based on Android platform with support of text and content offloading facilities. Furthermore, we investigate the performance of proposed model, and we conclude that Guidme model can optimize responsivity by leveraging public cloud server about 1.7% for light computation offloading and 11% while intensive computation offloading.