Technologies for thermal and power awareness and management in a multi-edge cloud networking environment
Technologies for managing Function-as-a-Service function requests based on thermal and power awareness include an edge entity device having a circuitry to receive, from an edge device, a request to execute a function in an edge network environment having a plurality of edge entities. The circuitry is also to evaluate thermal and power criteria associated with the request and determine, as a function of a predicted thermal output over a specified time period relative to thermal and power criteria, whether to execute the function. In response to a determination by the circuitry to not execute the function, the circuitry is to select an edge entity of a plurality of edge entities that is able to satisfy the thermal and power criteria. The circuitry is further to forward the request to the selected edge entity.
1. A device comprising:
at least one memory;
instructions; and
at least one processor to execute the instructions to:
in response to a request from a first edge entity of one or more edge entities in an edge network environment to execute a function, obtain energy criteria associated with the request;
predict first thermal properties of the device based on a predictive model;
distribute the predictive model to the one or more edge entities to cause execution of the distributed predictive model at the one or more edge entities;
obtain second thermal properties of the one or more edge entities based on the execution of the distributed predictive model at the one or more edge entities;
in response to the first thermal properties of the device satisfying the energy criteria, cause execution of the function by the device;
in response to the first thermal properties of the device not satisfying the energy criteria, select, based on the second thermal properties, a second edge entity from the one or more edge entities that is able to satisfy the energy criteria; and
forward the request to the second edge entity.
2. The device as defined in claim 1 , wherein the at least one processor is to execute the instructions to generate a map indicative of energy usage data obtained from the one or more edge entities, the at least one processor to select the second edge entity based on the map.
3. The device as defined in claim 2 , wherein the energy usage data corresponds to geographic locations of the one or more edge entities.
4. The device as defined in claim 3 , wherein the at least one processor is to execute the instructions to generate the map by populating a table stored in the memory, the table indicative of the second thermal properties associated with the one or more edge entities relative to the geographic locations of the one or more edge entities.
5. The edge entity device as defined in claim 2 , wherein the energy usage data includes ambient sensor data from edge resource components of the edge network environment, the ambient sensor data indicative of at least one of an energy harvested from the edge resource components, thermal metrics associated with the edge resource components, or battery power associated with the edge resource components.
6. The edge entity device as defined in claim 5 , wherein the energy usage data is generated based on the predictive model, the predictive model trained as a function of (a) the ambient sensor data and (b) historical sensor data associated with the edge resource components.
7. The device as defined in claim 5 , wherein the thermal metrics include at least one of temperature, humidity, or cooling rate of the edge resource components.
8. An apparatus comprising:
means for obtaining, in response to a request from a first edge entity of one or more edge entities in an edge network environment to execute a function, energy criteria associated with the request;
means for predicting first thermal properties of a device based on a predictive model;
means for distributing the predictive model to the one or more edge entities to cause execution of the distributed predictive model at the one or more edge entities;
means for obtaining second thermal properties of the one or more edge entities based on the execution of the distributed predictive model at the one or more edge entities;
means for causing execution of the function by the device when in response to the first thermal properties of the device satisfying the energy criteria;
means for selecting, in response to the first thermal properties of the device not satisfying the energy criteria, a second edge entity from the one or more edge entities that is able to satisfy the energy criteria; and
means for forwarding the request to the second edge entity.
9. The apparatus as defined in claim 8 , further including means for generating a map indicative of energy usage data obtained from the one or more edge entities, the map corresponding to geographic locations of the one or more edge entities.
10. The apparatus as defined in claim 9 , wherein the means for selecting the second edge entity selects the second edge entity based on the map and the geographic locations of the one or more edge entities.
11. The apparatus as defined in claim 10 , wherein the means for generating the map is to populate a table stored in memory, the table indicative of the second thermal properties associated with the one or more edge entities relative to the geographic locations of the one or more edge entities.
12. The apparatus as defined in claim 9 , wherein the means for selecting the second edge entity is to obtain ambient sensor data from edge resource components of the edge network environment, the ambient sensor data indicative of at least one of an energy harvested from the edge resource components, thermal metrics associated with the edge resource components, or battery power associated with the edge resource components.
13. The apparatus as defined in claim 12 , wherein the means for generating the map is to generate the energy usage data based on the predictive model, the predictive model trained as a function of (a) the ambient sensor data and (b) historical sensor data associated with the edge resource components.
14. The apparatus as defined in claim 12 , wherein the thermal metrics include at least one of temperature, humidity, or cooling rate of the edge resource components.
15. A non-transitory computer readable medium storing instructions that, when executed, cause at least one processor to at least:
in response to a request from a first edge entity of one or more edge entities in an edge network environment to execute a function, obtain energy criteria associated with the request;
predict first thermal properties of a device based on a predictive model;
distribute the predictive model to the one or more edge entities to cause execution of the distributed predictive model at the one or more edge entities;
obtain second thermal properties of the one or more edge entities based on the execution of the distributed predictive model at the one or more edge entities;
in response to the first thermal properties of the device satisfying the energy criteria, cause execution of the function by the device;
in response to the first thermal properties of the device not satisfying the energy criteria, select a second edge entity from the one or more edge entities that is able to satisfy the energy criteria; and
forward the request to the second edge entity.
16. The non-transitory computer readable medium as defined in claim 15 , wherein the instructions, when executed, cause the at least one processor to generate a map indicative of energy usage data obtained from the one or more edge entities, the energy usage data corresponding to geographic locations of the one or more edge entities.
17. The non-transitory computer readable medium as defined in claim 16 , wherein the instructions, when executed, cause the at least one processor to select the second edge entity based on the map.
18. The non-transitory computer readable medium as defined in claim 16 , wherein the instructions, when executed, cause the at least one processor to generate the map by populating a table stored in memory, the table indicative of the second thermal properties associated with the one or more edge entities relative to the geographic locations of the one or more edge entities.
19. The non-transitory computer readable medium as defined in claim 16 , wherein the energy usage data includes ambient sensor data from edge resource components of the edge network environment, the ambient sensor data indicative of at least one of an energy harvested from the edge resource components, thermal metrics associated with the edge resource components, or battery power associated with the edge resource components.
20. The non-transitory computer readable medium as defined in claim 19 , wherein the energy usage data is generated based on the predictive model, the predictive model trained as a function of (a) the ambient sensor data and (b) historical sensor data associated with the edge resource components.