USE TRIPLE H-AVATAR TECHNOLOGY FOR EDUCATION IN ONLINE MULTI-CLOUD PLATFORM LAB

Abstract

We presented a fast and scalable way to perform the exploration of online Multi-Cloud Platform Lab. model space. The acceleration achieved is much beyond what existing solutions can offer. Overall, the cloud computing model is a very good fit for the presented scenario. After processing of the thousand input data sets from HHH University, further efforts with online Multi-Cloud Platform Lab. modeling will require much less resource. The database is regularly updated, thus we can extract several hundred new input datasets every three months. This is less than 10% of the current data- base size, and so we will need a fraction of the resources to process it effectively. Also, the development of new model building and descriptor selection algorithms can be tested on a relatively small part of the input sets and for only the most promising ones the whole input data will be applied. Importantly, introducing new model building algorithms can reuse data from previous invocations reducing the need for large computing resources even more.