Data center infrastructure optimization method based on causal learning
Methods for active data center management by injecting randomized controlled signals in the operational controls of the cooling infrastructure of the data center and receiving response signals corresponding with the injected signals. The injected signals are used to adjust the operational controls of the cooling infrastructure, and the response signals relate to the operational conditions in the data center. Based upon the response signals along with independent and external variables, the randomized signals are continually injected into the cooling infrastructure and fine-tuned based upon the response signals. Optimum or improved parameters for controlling the cooling infrastructure of the data center are determined based upon the signal injections and corresponding responses.
1. A method for active data center management, comprising steps of:
injecting randomized controlled signals into operational controls of a data center;
ensuring the signal injections occur within normal operational ranges and constraints;
monitoring performance of operational conditions in the data center in response to the controlled signals;
computing confidence intervals about the causal relationships between the operational conditions and the controlled signals; and
selecting optimal signals for the operational controls of the data center based on the computed confidence intervals, wherein selecting further comprises selecting the optimal signals by probability matching where a frequency of assignment of the signals is determined by a mean of the confidence interval and an overlap of the confidence interval with other confidence intervals.
2. The method of claim 1 , wherein the injecting further comprises injecting the controlled signals to adjust parameters of cooling infrastructure for the data center.
3. The method of claim 1 , wherein the operational conditions comprise a temperature in the data center.
4. The method of claim 1 , wherein the injecting further comprises injecting the controlled signals into particular zones of the data center.
5. The method of claim 1 , wherein the normal operational ranges comprise a multidimensional space of possible control states generated based on control information and operational constraints.
6. The method of claim 1 , wherein the selecting further comprises selecting the optimal signals based upon external data.
7. The method of claim 1 , wherein the injecting further comprises blocking and balancing the randomized controlled signals across external variable states and minimizing carry over effects based on the measured spatial and temporal reach of effects.
8. The method of claim 1 , further comprising monitoring the performance over space and time.
9. The method of claim 1 , wherein the computing further comprises computing the confidence intervals within clusters to eliminate effect modifiers.
10. The method of claim 1 , wherein the signal injections have a spatial reach.
11. The method of claim 1 , wherein the signal injections have a temporal reach.
12. A method for active data center management, comprising:
providing signal injections for operational controls of cooling infrastructure of a data center, wherein each signal injection comprises a temporal reach and a spatial reach to compute causal relationships, wherein the spatial reach of each signal injection is a radius of influence of a particular control and the temporal reach of each signal injection is the response time of each signal injection comprising delays, fluctuations, and decay;
receiving response signals corresponding with the signal injections and operational conditions in the data center;
measuring a utility of the response signals;
accessing data relating to parameters for the operational controls of the cooling infrastructure of the data center; and
modifying the data for the operational controls based upon the utility of the response signals.
13. The method of claim 12 , wherein the providing further comprises adjusting parameters of the cooling infrastructure for the data center.
14. The method of claim 12 , wherein the receiving further comprises receiving a temperature in the data center.
15. The method of claim 12 , wherein the providing further comprises providing the signal injections into particular zones of the data center.
16. The method of claim 12 , wherein the modifying further comprises modifying the data for the operational controls based upon external data.
17. The method of claim 12 , wherein the signal injections are randomized.
18. At least one non-transitory data storage device storing instructions that, when executed, configure at least one processor to:
providing signal injections for operational controls of cooling infrastructure of a data center, wherein each signal injection comprises a temporal reach and a spatial reach to compute causal relationships, wherein the spatial reach of each signal injection is a radius of influence of a particular control and the temporal reach of each signal injection is the response time of each signal injection comprising at least one of delays, fluctuations, and decay;
receive response signals corresponding with the signal injections and operational conditions in the data center;
measure a utility of the response signals;
access data relating to parameters for the operational controls of the cooling infrastructure of the data center; and
modify the data for the operational controls based upon the utility of the response signals.
19. The at least one non-transitory data storage device of claim 18 , wherein the providing further comprises providing the signal injections into particular zones of the data center.
20. The at least one non-transitory data storage device of claim 18 , wherein the signal injections are randomized.