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KAIST Case Study

2018

The Bio-Information System Laboratory (BISL) in the Department of Bio and Brain Engineering at KAIST is a laboratory dedicated to the education and study of convergence technology based on computer science and biomedicine, with research topics including bioinformatics, health informatics, and data mining as its main focus. BISL is focusing on establishing the required rules of various biomedical phenomena through technical research on bio-data mining and system bioinformatics. KAIST Professor Doheon Lee, who manages BISL, has been actively pursuing the laboratory’s key research ever since becoming the director of the Bio-Synergy Research Center (www.biosynergy.re.kr), a national policy research project run by the government. This project is aimed at the development of original technology involving IT-BT fusion and convergence that can establish the multi-component, multi-target (MCMT) action principles of food and drugs in the human body through a virtual human body system.

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As a developer, I found AWS to be very convenient. In our previous development environment, we had to stop services when we needed to update them. With CodeCommit or similar services on AWS, however, you can update services without stopping them. Moreover, a blockchain consists of many nodes. With our existing servers, you would have to newly configure a server whenever these nodes increased. Because using AWS eliminated this workload, however, it was very convenient.”

Junseok Park
Researcher, KAIST

The Challenge

BISL is currently conducting Collaborative Research for Us (CORUS; corus.kaist.edu) as part of the Challenge Project to verify human body efficacy in the virtual human body system. CORUS is being conducted in the form of citizen science with the voluntary participation of the general public, who provide the information necessary for research and are rewarded in return with cryptocurrency through the blockchain network. For this encrypted reward system, security and transaction integrity must be guaranteed. It was also impossible for the laboratory to provide a platform with user convenience as a priority because of its limited IT manpower compared to the number of citizens participating in the project. Therefore, BISL needed a solution that could be managed by a small number of personnel and which would provide high levels of both security and user convenience.

Why Amazon Web Services

It was concluded that enabling the researchers to focus on their research would be more effective than having them configure a physical server and development environment. To find a cloud solution that would provide security and safety as well as manageability with low overhead, KAIST investigated cloud solutions worldwide. In the end, they chose AWS, which can be easily accessed by general users as well as developers. “We made inquiries with several global companies, but only AWS gave a very positive response, sharing their ideas and relevant technical solutions with us,” says Junseok Park, a PhD student and researcher at BISL in the Department of Bio and Brain Engineering at KAIST. “This positive response from AWS is one of the reasons we chose it. In addition, AWS can be easily accessed by general users so it meets the requirements of the project we are implementing, unlike other solutions that work for developers only.”

Currently, the CORUS project runs on AWS. The PostgreSQL server, Docker, and other components were all relocated to Amazon Relational Database Service (RDS) and Amazon Elastic Container Service (ECS). For the creation and transfer of cryptocurrencies requiring data safety, transaction integrity was ensured through Amazon Simple Queue Service (SQS), Amazon Simple Notification Service (SNS), and AWS Lambda. Due to its high level of safety and availability, Amazon Simple Storage Service (Amazon S3) is used as a data repository. Meanwhile, Amazon EMR is used for high-volume data analysis. Amazon CloudWatch is used for monitoring the entire system, and Amazon EC2 Auto Scaling for ensuring availability. AWS CodeCommit, AWS CodeDeploy, and AWS CodePipeline are used for developing, storing, and deploying code.

The Benefits

It was concluded that enabling the researchers to focus on their research would be more effective than having them configure a physical server and development environment. To find a cloud solution that would provide security and safety as well as manageability with low overhead, KAIST investigated cloud solutions worldwide. In the end, they chose AWS, which can be easily accessed by general users as well as developers. “We made inquiries with several global companies, but only AWS gave a very positive response, sharing their ideas and relevant technical solutions with us,” says Junseok Park, a PhD student and researcher at BISL in the Department of Bio and Brain Engineering at KAIST. “This positive response from AWS is one of the reasons we chose it. In addition, AWS can be easily accessed by general users so it meets the requirements of the project we are implementing, unlike other solutions that work for developers only.”

Currently, the CORUS project runs on AWS. The PostgreSQL server, Docker, and other components were all relocated to Amazon Relational Database Service (RDS) and Amazon Elastic Container Service (ECS). For the creation and transfer of cryptocurrencies requiring data safety, transaction integrity was ensured through Amazon Simple Queue Service (SQS), Amazon Simple Notification Service (SNS), and AWS Lambda. Due to its high level of safety and availability, Amazon Simple Storage Service (Amazon S3) is used as a data repository. Meanwhile, Amazon EMR is used for high-volume data analysis. Amazon CloudWatch is used for monitoring the entire system, and Amazon EC2 Auto Scaling for ensuring availability. AWS CodeCommit, AWS CodeDeploy, and AWS CodePipeline are used for developing, storing, and deploying code.

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About KAIST

The Bio-Information System Laboratory (BISL) in the Department of Bio and Brain Engineering at KAIST is a laboratory dedicated to the education and study of convergence technology based on computer science and biomedicine, with research topics including bioinformatics, health informatics, and data mining as its main focus.


AWS Services Used

Amazon S3

Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. 

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Amazon RDS

Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud.

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Amazon ECS

Amazon Elastic Container Service (Amazon ECS) is a highly scalable, high-performance container orchestration service that supports Docker containers.

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Amazon SQS

Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications.

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