Dynamic resource management for stream analytics
AssigneeNEC Corporation
InventorsGiuseppe Coviello, Kunal Rao, Srimat Chakradhar, Priscilla Benedetti
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Abstract
A computer implemented method is provided for resource management of stream analytics at each individual node that includes computing a mean of output processing rate of microservices in a pipeline; and evaluating a state of each microservice of the microservices in the pipeline. The computer implemented method also includes selecting a single microservice from the pipeline for updating resources for an action that changes the state in single the microservice that is selected; and performing resource allocation update for the selected microservice. The computer implemented method may also include updating the state of the selected microservice.
Claims16
A computer implemented method for resource management of stream analytics at each individual node comprising:
- computing a mean of output processing rate of microservices in a pipeline;
- evaluating a state of each microservice of the microservices in the pipeline, wherein the evaluating of the state employs a Q-learning workflow of a reinforcement learning (RL) method;
- selecting a single microservice from the pipeline for updating resources for an action that changes the state in the single microservice that is selected, wherein in exploitation mode the microservice with a maximum Q-value is selected from the Q-learning workflow, wherein a Q-value illustrates a positive change in state for an allocation change;
- performing resource allocation updates for the selected microservice;
- and
- updating the state of the selected microservice with a chosen resource allocation.
A system for resource management of stream analytics at each individual node comprising:
- a hardware processor;
- and
- a memory that stores a computer program product, the computer program product when executed by the hardware processor, causes the hardware processor to:
- compute a mean of output processing rate of microservices in a pipeline;
- evaluate a state of each microservice of the microservices in the pipeline, wherein the evaluate of the state employs a Q-learning workflow of a reinforcement learning (RL) method;
- select a single microservice from the pipeline for updating resources for an action that changes the state in the single microservice that is selected, wherein in exploitation mode the microservice with a maximum Q-value is selected from the Q-learning workflow, where a Q-value illustrates a positive change in state for an allocation change;
- perform resource allocation updates for the selected microservice;
- and
- update the state of the selected microservice with a chosen resource allocation.
A computer program product for resource management of stream analytics at each individual node comprising a computer readable storage medium having computer readable program code embodied therewith the computer readable program code executable by a hardware processor to cause the hardware processor to:
- compute, using the hardware processor, a mean of output processing rate of microservices in pipeline of edge node;
- evaluate, using the hardware processor, a state of each microservice of the microservices in the pipeline, wherein the evaluate of the state employs a Q-learning workflow of a reinforcement learning (RL) method;
- select, using the hardware processor, a single microservice from the pipeline for updating resources for an action that changes the state in the single microservice that is selected, wherein in exploitation mode the microservice with a maximum Q-value is selected from the Q-learning workflow, wherein a Q-value illustrates a positive change in state for an allocation change;
- perform, using the hardware processor, resource allocation update for the selected microservice;
- and
- update, using the hardware processor, the state of the selected microservice with a chosen resource allocation.
Dependencies are inferred from the claim text.