Representing sensor data as binary decision diagrams

• US 8,874,607 B2
• Filed: 08/17/2010
• Issued: 10/28/2014
• Est. Priority Date: 08/17/2010
• Status: Active Grant

• Current Assignee: Fujitsu Limited
• Original Assignee: Fujitsu Limited
• Inventors: Stergiou, Stergios, Jain, Jawahar
• Primary Examiner(s): SYED, FARHAN M
• Application Number:
  US12/857,594
• Publication Number:
  US 20120046913A1
• Time in Patent Office: 1,533 Days
• US Class Current: 707/769
• CPC Class Codes: G06F 16/9014 hash tables

Abstract

According to certain embodiments, a set of samples of sensor data is accessed. The set of samples records measurements taken by one or more sensors. Each sample is represented as a minterm to yield a set of minterms. A characteristic function is generated from the set of minterms. The characteristic function indicates whether a given minterm is a member of the set of minterms.

Claims

1. A computer-implemented method comprising:

accessing, by at least one computer processor, a set of samples of sensor data recording a plurality of measurements taken by one or more sensors;

representing, by the at least one computer processor, each data value of the set of samples of the sensor data as a minterm to yield a set of minterms, each minterm within the set of minterms comprising a logical expression of one or more variables allocated to the data value of the sample of the sensor data;

generating, by the at least one computer processor, a first binary decision diagram (BDD) from the set of minterms by applying a logical OR operation to the minterms of the set of minterms to generate the first BDD, the first BDD indicating whether a given minterm is a member of the set of minterms, wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function; and

annotating the first BDD by applying a logical AND operation to the first BDD and a second BDD, the second BDD representing one or more data values of sensor data that are associated with a given annotation.

2. The computer-implemented method of claim 1, each sample comprising a tuple of one or more sensor values, each sensor value recording one or more measurements taken by one or more sensors at a parameter value of a parameter.

3. The computer-implemented method of claim 2, the parameter representing a time, a temperature, or a location.

4. The computer-implemented method of claim 1, the representing each sample of the set further comprising:

receiving the each sample, the each sample comprising one or more sensor values; and

for each sensor value, expressing the sensor value as a binary number using one or more variables allocated to the each sensor value to yield one or more binary numbers.

5. The computer-implemented method of claim 1, further comprising:

accessing a set of next samples of sensor data;

representing each next sample as a next minterm to yield a set of next minterms; and

updating the first BDD according to the set of next minterms.

6. The computer-implemented method of claim 1, further comprising:

accessing a set of next samples of sensor data;

representing each next sample as a next minterm to yield a set of next minterms; and

applying a logical OR operation to the first BDD and next minterms of the set of next minterms to yield an updated first BDD.

19. The computer-implemented method of claim 1, wherein accessing the set of samples of sensor data comprises accessing the set of samples in a database, and wherein the method further comprises:

receiving a search query for one or more requested values; and

formulating, by the at least one computer processor, a query function representing the one or more requested values and the binary decision diagram; and

executing the query function representing the one or more requested values and the binary decision diagram on the set of samples stored in the database to identify one or more measurements that include the one or more requested values.

20. The computer-implemented method of claim 1, wherein the sensor measurement data comprises medical measurement data taken by one or more medical sensors.

7. An apparatus comprising:

one or more processors; and

a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to;

access a set of samples of sensor data recording a plurality of measurements taken by one or more sensors;

represent each data value of the set of samples of the sensor data as a minterm to yield a set of minterms, each minterm within the set of minterms comprising a logical expression of one or more variables allocated to the data value of the sample of the sensor data;

generate a first binary decision diagram (BDD) from the set of minterms by applying a logical OR operation to the minterms of the set of minterms to generate the first BDD, the first BDD indicating whether a given minterm is a member of the set of minterms, wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function; and

annotate the first BDD by applying a logical AND operation to the first BDD and a second BDD, the second BDD representing one or more data values of sensor data that are associated with a given annotation.

8. The apparatus of claim 7, each sample comprising a tuple of one or more sensor values, each sensor value recording one or more measurements taken by one or more sensors at a parameter value of a parameter.

9. The apparatus of claim 8, the parameter representing a time, a temperature, or a location.

10. The apparatus of claim 7, the representing each sample of the set further comprising:

receiving the each sample, the each sample comprising one or more sensor values; and

for each sensor value, expressing the sensor value as a binary number using one or more variables allocated to the each sensor value to yield one or more binary numbers.

11. The apparatus of claim 7, the one or more processors further configured to:

access a set of next samples of sensor data;

represent each next sample as a next minterm to yield a set of next minterms; and

update the first BDD according to the set of next minterms.

12. The apparatus of claim 7, the one or more processors further configured to:

access a set of next samples of sensor data;

represent each next sample as a next minterm to yield a set of next minterms; and

apply a logical OR operation to the first BDD and next minterms of the set of next minterms to yield an updated first BDD.

13. One or more non-transitory computer-readable media storing code, when executed by one or more processors, configured to:

access a set of samples of sensor data recording a plurality of measurements taken by one or more sensors;

represent each data value of the set of samples of the sensor data as a minterm to yield a set of minterms, each minterm within the set of minterms comprising a logical expression of one or more variables allocated to the data value of the sample of the sensor data;

generate a first binary decision diagram (BDD) from the set of minterms by applying a logical OR operation to the minterms of the set of minterms to generate the first BDD, the first BDD indicating whether a given minterm is a member of the set of minterms, wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function; and

annotate the first BDD by applying a logical AND operation to the first BDD and a second BDD, the second BDD representing one or more data values of sensor data that are associated with a given annotation.

14. The media of claim 13, each sample comprising a tuple of one or more sensor values, each sensor value recording one or more measurements taken by one or more sensors at a parameter value of a parameter.

15. The media of claim 13, the parameter representing a time, a temperature, or a location.

16. The media of claim 13, the representing each sample of the set further comprising:

receiving the each sample, the each sample comprising one or more sensor values; and

for each sensor value, expressing the sensor value as a binary number using one or more variables allocated to the each sensor value to yield one or more binary numbers.

17. The media of claim 13, the code further configured to:

access a set of next samples of sensor data;

represent each next sample as a next minterm to yield a set of next minterms; and

update the first BDD according to the set of next minterms.

18. The media of claim 13, the code further configured to:

access a set of next samples of sensor data;

represent each next sample as a next minterm to yield a set of next minterms; and

apply a logical OR operation to the first BDD and next minterms of the set of next minterms to yield an updated first BDD.