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MIT Geospatial Data Center

The MIT Geospatial Data Center is the uniting force of MIT's Auto-ID labs, the Geonumerics Group, the Center for Grid Computing, and the Intelligent Engineering Systems Laboratory.
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Cyberphysical Security

Large In-Memory Cyber-Physical Security-Related Analytics via Scalable Coherent Shared Memory Architectures
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Tackling Big Data

GDC’s Large-Scale Simulator for Global Data Infrastructure Optimization tackles Big Data
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MIT Simulator

"Predicting the performance of these systems is extremely difficult”, says Williams, the Director of MIT Geospatial Data Center. To address these questions we have built a simulator so companies can test potential solutions before.
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The Internet of Things

Connecting the physical and the virtual world
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GDC is always looking for strong students and researchers. A strong preference is given to students who have been admitted to MIT. Similarly, research assistant positions are typically filled internally by graduate students.

Applied Cyber Security Course

Date: June 23-24, 2014. The course covers securing computers, applications, networks, digital forensics, and the ethical and legal practices affecting all computer users. The course also covers the strategies, implementation and management of a business information continuity plan, mitigation of cyber vulnerabilities, and incident response and analysis. The content is targeted at ensuring the privacy, reliability, and integrity of information systems

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Cyber-Physical Security

Cyber-physical security-related queries and analytics run on traditional relational databases can take many hours to return. Furthermore, programming analytics on distributed databases requires great skill, and there is a shortage of such talent worldwide. In this talk on computational intelligence within cyber security, we will review developments of processing large datasets in-memory using a coherent shared memory approach. The coherent shared memory approach allows programmers to view a cluster of servers as a system with a single large RAM.

Big Data Lab

To evaluate the impact of ”what if” scenarios on the performance availability and reliability of the system a Big Data infrastructure simulator has been architected. The goal is to provide datacenter operators with a tool that allows understanding and predicting the consequences of the deployment of new network topologies, hardware configurations or software applications in a global data infrastructure, without affecting the service. The simulator was validated on the data infrastructure of a Fortune 500 company.

Data Center Infrastructure Simulator

"Predicting the performance of these systems is extremely difficult", says Williams, the Director of MIT Geospatial Data Center. To address these questions we have built a simulator so companies can test potential solutions before spending the money to purchase. "We built the MIT Global Infrastructure Simulator so we could accurately predict performance and detect vulnerabilities in global IT systems," says Sanchez, MIT's GDC Executive Director and Chief Architect. "The simulator has been tested by a Global 100 company with excellent results."