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Cloud without borders

Cloud without borders . Dr. Yelena Yesha Director of UMBC site NSF CHMPR Computer Science and Electrical Engineering University of Maryland, Baltimore County. Cloud computing. Cloud Security Tightening of Cloud access Private Clouds Openness and no borders

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Cloud without borders

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  1. Cloud without borders Dr. Yelena Yesha Director of UMBC site NSF CHMPR Computer Science and Electrical Engineering University of Maryland, Baltimore County

  2. Cloud computing • Cloud Security • Tightening of Cloud access • Private Clouds • Openness and no borders • Better collaboration between organizations • Academia can be an early adoptee of Open Clouds • Stanford professors teaching AI course to 160,000 people worldwide.

  3. Global Clouds • Spanning multiple continents • Multiple language support • Multiple policysupport • Cloud Location – EU, US jurisdiction • Different business practices issues • Knowledge of international treaties and homeland security issues

  4. Working Together to Build a Healthy Cloud Ecosystem • Scientists/ Professors working more on inter-disciplinary researchand need to share data • Same research area, different domains OR different research area, same project. • E.g. Research on NOAA weather prediction models and Personalized medicine being conducted by same team • Virtualization and Multi-tenancy of Clouds enable researchers working on the same project across different research areas. • Our team works on data mining and the team in UCSD looks at data visualization referring to the same data on the cloud.

  5. Cloud sharing : Community Clouds • Built a community cloud across multiple Universities • UCSD, Georgia Tech, FAU • Cloud infrastructure shared to run HPC experiments • Hybrid clouds will be needed to manage legacy systems • Legacy code will remain on internal infrastructure • Data/ Results can be shared on public/community clouds

  6. Roadblocks • Cloud security – multi-tenancy • Data portability difficult across difference cloud platforms. • Manual Migration (Trucking disks of data) appears to be the fastest mode of migrating large volume of data. • Scientific research data is usually large volume data.

  7. Prototype Automatic acquisition and composition of Storage service on the Cloud www.cs.umbc.edu/~kjoshi1/nist_demo/prototype_video.mp4

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