Networking Infiniband. High bandwidth 3D Torus. Software Charm++, MPI Big Data Data Source Generated from synthetic population generator. Currently Characteristics (distributed/centralized) centralized. However, could be made distributed as part of post-processing. Volume (size) 100TB Velocity Interactions with experts and visualization routines (e.g. real time) generate large amount of real time data. Data feeding into the simulation is small but data generated by simulation is massive. Variety Variety depends upon the complexity of the model over (multiple datasets, which the simulation is being performed. Can be very mashup) complex if other aspects of the world population such as type of activity, geographical, socio-economic, cultural variations are taken into account. Variability (rate of Depends upon the evolution of the model and change) corresponding changes in the code. This is complex and time intensive. Hence low rate of change. Big Data Science Veracity (Robustness Robustness of the simulation is upon the (collection, curation, Issues, semantics) quality of the model. However, robustness of the analysis, computation itself, although non-trivial, is tractable. action) Visualization Would require very large amount of movement of data to enable visualization. Data Quality (syntax) Consistent due to generation from a model Data Types Primarily network data. Data Analytics Summary of various runs and replicates of a simulation Big Data Specific Computation of the simulation is both compute intensive and data intensive. Challenges (Gaps) Moreover, due to unstructured and irregular nature of graph processing the problem is not easily decomposable. Therefore it is also bandwidth intensive. Hence, a supercomputer is applicable than cloud type clusters. Big Data Specific None Challenges in Mobility Security and Privacy Several issues at the synthetic population-modeling phase (see social contagion model). Requirements Highlight issues for In general contagion diffusion of various kinds: information, diseases, social unrest can generalizing this use be modeled and computed. All of them are agent-based model that utilize the case (e.g. for ref. underlying interaction network to study the evolution of the desired phenomena. architecture) More Information (URLs) Healthcare and Life Sciences> Use Case 24: Social Contagion Modeling Use Case Title Social Contagion Modeling
Networking Infiniband. High bandwidth 3D Torus. Software Charm++, MPI Big Data Characteristics Data Source (distributed/centralized) Generated from synthetic population generator. Currently centralized. However, could be made distributed as part of post-processing. Volume (size) 100TB Velocity (e.g. real time) Interactions with experts and visualization routines generate large amount of real time data. Data feeding into the simulation is small but data generated by simulation is massive. Variety (multiple datasets, mashup) Variety depends upon the complexity of the model over which the simulation is being performed. Can be very complex if other aspects of the world population such as type of activity, geographical, socio-economic, cultural variations are taken into account. Variability (rate of change) Depends upon the evolution of the model and corresponding changes in the code. This is complex and time intensive. Hence low rate of change. Big Data Science (collection, curation, analysis, action) Veracity (Robustness Issues, semantics) Robustness of the simulation is upon the quality of the model. However, robustness of the computation itself, although non-trivial, is tractable. Visualization Would require very large amount of movement of data to enable visualization. Data Quality (syntax) Consistent due to generation from a model Data Types Primarily network data. Data Analytics Summary of various runs and replicates of a simulation Big Data Specific Challenges (Gaps) Computation of the simulation is both compute intensive and data intensive. Moreover, due to unstructured and irregular nature of graph processing the problem is not easily decomposable. Therefore it is also bandwidth intensive. Hence, a supercomputer is applicable than cloud type clusters. Big Data Specific Challenges in Mobility None Security and Privacy Requirements Several issues at the synthetic population-modeling phase (see social contagion model). Highlight issues for generalizing this use case (e.g. for ref. architecture) In general contagion diffusion of various kinds: information, diseases, social unrest can be modeled and computed. All of them are agent-based model that utilize the underlying interaction network to study the evolution of the desired phenomena. More Information (URLs) Healthcare and Life Sciences> Use Case 24: Social Contagion Modeling Use Case Title Social Contagion Modeling