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Research cloud computing

Research Infrastructure as a Service
​Providing Research Infrastructure as a Service, the University of Sustainability offers a cloud solution for smart research infrastructure and technology providers to quickly build stable, cost-efficient, and reliable ubiquitous research platforms.
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IoT Solution
Build innovative applications to gather, process, analyze, and act on data generated by connected scientific instrumentation,  equipment and devices, without maintaining a separate infrastructure.
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Take your smart research infrastructure to the next level with stable, cost-efficient, smooth, and reliable cloud services. This lets you quickly build bespoke solutions with fully integrated, data-driven and highly scalable cloud computing solutions.

Smart Hardware Solution
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The University for Sustainability offers intelligent IoT cloud solutions which integrate with your smart  scientific equipment, hardware devices and provide real-time data to establish an instant exchange of information between the hardware and web application. This provides essential data which can be processed in real-time accelerating insightful research. 

Solution Architecture
The smart hardware platform of University for Sustainability Research Cloud consists of six steps:
  1. Hardware equipment stage: At this stage, it connects smart research equipment to a gateway for data exchange using online communication applications and modules such as a Multipoint Control Unit, sensors and Wi-Fi/4G/5G sensors.
  2. Cloud gateway stage: At this stage, the cloud gateway receives and forwards messages from connected intelligent hardware equipment to independent nodes through universal protocols.
  3. Mobile client: At this stage, the IoT cloud platform receives and sends data back and forth to the cloud gateway and also processes equipment registration queries, data storage, data processing and sends relevant commands.
  4. IoT stage:  At the IoT stage, the Server Load Balancer and a horizontally scalable ECS cluster push and receive high-quality concurrent data structures.
  5. Service stage: At the service stage, nodes match the target hardware and forwards service data on the basis of parameters set by user. This forwarding completes data subscription and distribution of the service system and allows you to control hardware efficiently.
  6. Big data stage: At the big-data stage, huge sets of transactional data generated by users which are stored in the  Distributed Relational Database provides real-time response to queries. University for Sustainability Advanced Analytics performs various statistical analyses and provides intelligent predictions based on analyzed data