US 11,055,630 B2
Multitemporal data analysis
Jason Crabtree, Vienna, VA (US); and Andrew Sellers, Monument, CO (US)
Assigned to QOMPLX, Inc., Tysons, VA (US)
Filed by QOMPLX, Inc., Tysons, VA (US)
Filed on Oct. 23, 2017, as Appl. No. 15/790,206.
Application 15/790,206 is a continuation in part of application No. 15/616,427, filed on Jun. 7, 2017.
Application 15/616,427 is a continuation in part of application No. 14/925,974, filed on Oct. 28, 2015, abandoned.
Claims priority of provisional application 62/569,362, filed on Oct. 6, 2017.
Prior Publication US 2018/0181537 A1, Jun. 28, 2018
Int. Cl. G06N 5/02 (2006.01); G06N 20/00 (2019.01); G06F 16/90 (2019.01); G06F 16/25 (2019.01); H04L 29/08 (2006.01)
CPC G06N 20/00 (2019.01) [G06F 16/252 (2019.01); G06F 16/90 (2019.01); G06N 5/022 (2013.01); H04L 67/10 (2013.01)] 12 Claims
OG exemplary drawing
 
1. A system for multitemporal data analysis, comprising:
a computing device comprising a memory, a processor, and a non-volatile data storage device;
a directed computational graph service module comprising a first plurality of programming instructions stored in the memory and operable on the processor, wherein the first plurality of programming instructions, when operating on the processor, causes the computing device to:
receive input data, the input data comprising a combination of stored data and streaming data;
convert the input data into a directed computational graph, wherein:
the directed computational graph comprises nodes representing data transformations and edges representing messaging between the nodes;
the data transformation of each node is shared among a plurality of instantiated workers; and
the nodes, edges, and instantiated workers of the directed computational graph represent state information for processing of the input data; analyze the directed computational graph to determine whether to batch process or real-time process portions of the input data based on measuring shared state information among the nodes, edges, and instantiated workers of the directed computational graph; and
reorganize the input data into batch processing data for queueing to a general transformer service module or real-time processing data for queueing to a decomposable transformer service module based on the analysis of the directed computational graph;
a general transformer service module comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to:
receive the batch processing data from the directed computational graph service module; and
perform batch processing of the batch processing data according to a pre-determined first data processing workflow; and
a decomposable transformer service module comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to:
receive the real-time processing data from the directed computational graph service module; and
perform real-time processing of the real-time processing data according to a pre-determined second data processing workflow.