Data reduction techniques for a multi-sensor internet of things environment
Data reduction techniques are provided for a multi-sensor IoT environment. An exemplary method comprises: dynamically determining, by a device within a distributed network comprised of a plurality of sensors, an amount of sensor data to be collected by and/or transmitted by a sensor within the distributed network based on at least one predefined spatial-based rule and/or at least one predefined temporal-based rule; and processing the sensor data based on the dynamically determined amount of sensor data. A percentage of the plurality of sensors within the distributed network that collect and/or transmit the sensor data can optionally be specified. One or more sensors optionally collect the sensor data at a default resolution and a predefined spatial-based rule and/or a predefined temporal-based rule specifies a predefined trigger for at least one sensor to collect and/or transmit the sensor data at a higher resolution.
1. A method, comprising:
dynamically determining, by at least one processing device within a distributed network comprised of a plurality of sensors, an amount of sensor data to be transmitted by at least one of the plurality of sensors within the distributed network based at least in part on one or more of: (i) at least one predefined spatial-based rule that specifies the amount of sensor data to be transmitted by the at least one sensor based at least in part on one or more of: (a) a location of one or more of the sensors with respect to a geographic location of a point of interest being evaluated in the sensor data and (b) a proximity of two or more of the sensors with respect to one another, and (ii) at least one predefined temporal-based rule that specifies the amount of sensor data to be transmitted by the at least one sensor based at least in part on a time difference between a plurality of samples of the sensor data, wherein the one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule evaluate at least one data element received from one or more of the plurality of sensors; and
processing, by the at least one processing device, the sensor data based on the dynamically determined amount of sensor data.
2. The method of claim 1 , wherein the sensors within the distributed network are identified based on one or more of a direct transmission radius between the sensors, a radius between the sensors, and one or more of a trajectory and location of the sensors.
3. The method of claim 1 , wherein one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule specify a percentage of the plurality of sensors within the distributed network that one or more of collect and transmit the sensor data.
4. The method of claim 1 , wherein the at least one predefined spatial-based rule specifies a sampling resolution of the sensor data one or more of collected by and transmitted by one or more of the plurality of sensors within the distributed network based on a distance of the one or more sensors from a point of interest.
5. The method of claim 1 , wherein one or more of the plurality of sensors collect the sensor data at a default resolution and wherein one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule specifies a predefined trigger for at least one sensor to one or more of collect and transmit the sensor data at a higher resolution.
6. The method of claim 1 , wherein the at least one predefined spatial-based rule specifies a resolution for the one or more sensors to one or more of collect and transmit the sensor data based on a predefined local sensor density.
7. The method of claim 1 , wherein the at least one predefined temporal-based rule specifies a particular time for the plurality of sensors within the distributed network to collect the sensor data.
8. The method of claim 1 , wherein one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule are based on one or more predefined policies.
9. A system, comprising:
a memory; and
at least one processing device, coupled to the memory, operative to implement the following steps:
dynamically determining, by the at least one processing device within a distributed network comprised of a plurality of sensors, an amount of sensor data to be transmitted by at least one of the plurality of sensors within the distributed network based at least in part on one or more of: (i) at least one predefined spatial-based rule that specifies the amount of sensor data to be transmitted by the at least one sensor based at least in part on one or more of: (a) a location of one or more of the sensors with respect to a geographic location of a point of interest being evaluated in the sensor data and (b) a proximity of two or more of the sensors with respect to one another, and (ii) at least one predefined temporal-based rule that specifies the amount of sensor data to be transmitted by the at least one sensor based at least in part on a time difference between a plurality of samples of the sensor data, wherein the one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule evaluate at least one data element received from one or more of the plurality of sensors; and
processing, by the at least one processing device, the sensor data based on the dynamically determined amount of sensor data.
10. The system of claim 9 , wherein one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule specify a percentage of the plurality of sensors within the distributed network that one or more of collect and transmit the sensor data.
11. The system of claim 9 , wherein the at least one predefined spatial-based rule specifies a sampling resolution of the sensor data one or more of collected by and transmitted by one or more of the plurality of sensors within the distributed network based on a distance of the one or more sensors from a point of interest.
12. The system of claim 9 , wherein one or more of the plurality of sensors collect the sensor data at a default resolution and wherein one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule specifies a predefined trigger for at least one sensor to one or more of collect and transmit the sensor data at a higher resolution.
13. The system of claim 9 , wherein the at least one predefined spatial-based rule specifies a resolution for the one or more sensors to one or more of collect and transmit the sensor data based on a predefined local sensor density.
14. The system of claim 9 , wherein one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule are based on one or more predefined policies.
15. A computer program product, comprising a non-transitory machine-readable storage medium having encoded therein executable code of one or more software programs, wherein the one or more software programs when executed by at least one processing device perform the following steps:
dynamically determining, by the at least one processing device within a distributed network comprised of a plurality of sensors, an amount of sensor data to be transmitted by at least one of the plurality of sensors within the distributed network based at least in part on one or more of: (i) at least one predefined spatial-based rule that specifies the amount of sensor data to be transmitted by the at least one sensor based at least in part on one or more of: (a) a location of one or more of the sensors with respect to a geographic location of a point of interest being evaluated in the sensor data and (b) a proximity of two or more of the sensors with respect to one another, and (ii) at least one predefined temporal-based rule that specifies the amount of sensor data to be transmitted by the at least one sensor based at least in part on a time difference between a plurality of samples of the sensor data, wherein the one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule evaluate at least one data element received from one or more of the plurality of sensors; and
processing, by the at least one processing device, the sensor data based on the dynamically determined amount of sensor data.
16. The computer program product of claim 15 , wherein one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule specify a percentage of the plurality of sensors within the distributed network that one or more of collect and transmit the sensor data.
17. The computer program product of claim 15 , wherein the at least one predefined spatial-based rule specifies a sampling resolution of the sensor data one or more of collected by and transmitted by one or more sensors within the distributed network based on a distance of the one or more of the plurality of sensors from a point of interest.
18. The computer program product of claim 15 , wherein one or more of the plurality of sensors collect the sensor data at a default resolution and wherein one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule specifies a predefined trigger for at least one sensor to one or more of collect and transmit the sensor data at a higher resolution.
19. The computer program product of claim 15 , wherein the at least one predefined spatial-based rule specifies a resolution for the one or more sensors to one or more of collect and transmit the sensor data based on a predefined local sensor density.
20. The computer program product of claim 15 , wherein one or more of the at least one predefined spatial-based rule and the at least one predefined temporal-based rule are based on one or more predefined policies.