Pierre Mouallem

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The emergence of leadership class computing is creating a tsunami of data from petascale simulations. Results are typically analyzed by dozens of scientists. In order for the scientist to digest the vast amount of data being produced from the simulations and auxiliary programs, it is critical to automate the effort to manage, analyze, visualize, and share(More)
Comprehensive, end-to-end, data and workflow management solutions are needed to handle the increasing complexity of processes and data volumes associated with modern distributed scientific problem solving, such as ultra-scale simulations and high-throughput experiments. The key to the solution is an integrated network-based framework that is functional,(More)
Collaboratively monitoring and analyzing large scale simulations from petascale computers is an important area of research and development within the scientific community. This paper addresses these issues when teams of colleagues from different research areas work together to help understand the complex data generated from these simulations. In particular,(More)
Determining mission-aware criticality, dependency, and resilience of cyber assets is required to support mission assurance in cyber defense and continuous operation of networks. This paper addresses the characterization of mission-aware asset criticality and the real-time dependencies of assets, services, tasks, and missions using Time Petri Nets and impact(More)
Alert Aggregation in mobile networks plays an important role in mitigating the adverse impact of alert generation by reducing the amount of communication and security data to be transmitted. However, it is not guaranteed that the bandwidth necessary to transmit all aggregated alerts is always available, which usually result in the transmission of a portion(More)
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