Method of optimizing energy utilization in a service-based architecture (sba) based wireless network

US2026046198A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2026046198-A1
Application numberUS-202519295091-A
CountryUS
Kind codeA1
Filing dateAug 8, 2025
Priority dateAug 9, 2024
Publication dateFeb 12, 2026
Grant date

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Abstract

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The evolution of mobile networks marks a significant leap in communication technologies, driven by the demand for high data rates, ultra-low latency, and enhanced connectivity. A key enabler in 5G is the adoption of Micro Service Based Architecture. Microservice Based Architecture decomposes the complex functionality of 5G Core Network into smaller Network Functions (NFs) that are microservice-based. Microservices provide numerous advantages such as ease of distribution and isolated updates. One of the biggest advantages of microservices is scalability and fault tolerance. But when we look at the future mobile network one alarming concern is sustainability. The energy consumed by these mobile networks is enormous along with that add up the CO2 emissions. An Energy Optimization Controller (EOC) collects energy statistics for the Network per slice/QoS/NF/UE level. It calculates energy efficiency and optimizes by dynamically managing the network.

First claim

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1 - 13 . (canceled) 14 . A method of optimizing energy utilization in a service-based architecture (SBA) based wireless network, the method comprising: receiving, by an energy optimization controller (EOC), a first power consumption information of a network function instance, wherein the first power consumption is the power consumed by the network function instance; determining, by the EOC, if the first power consumption is above a first threshold; obtaining, by the EOC, energy information of plurality of microservices of the network function instance, wherein the energy information comprises information related to power consumed by the plurality of microservices; classifying, by the EOC, each of the plurality of microservices based on the received energy information as one of: a high energy utilized microservice, a medium energy utilized microservice, and a low energy utilized microservice; retrieving, by the EOC, at least one microservice classified as the low energy utilized microservice; classifying, by the EOC, at least one low energy utilized microservice based on priority level, wherein the priority level is one of: a low priority, and a high priority; identifying, by the EOC, at least one low priority microservices; selecting, by the EOC, at least one microservice of interest; informing by the EOC, at least one microservice of interest to the network function instance; and changing, by the network function instance, an operating status of the at least one microservice of interest in the network function instances to de-active. 15 . The method as claimed in claim 14 , wherein identifying, by the EOC, at least one low priority microservices further comprises of identifying at least one low latency microservices from at least one low priority microservices having latencies below a second threshold. 16 . The method as claimed in claim 14 , wherein classifying, by the EOC, each of the plurality of microservices is predefined by an operator. 17 . The method as claimed in claim 14 , wherein selecting, by the EOC, at least one microservice of interest, is performed when a second power consumption is greater than a sum of a third power consumption and a fourth power consumption of the at least one low priority microservice wherein, the second power consumption is the power required for the selected microservice when its operating status is idle, the third power consumption is the power required for the selected microservice for changing the operating status to active, and the fourth power consumption is the power required for the selected microservice for changing the operating status to de-active. 18 . The method as claimed in claim 17 , wherein the second power consumption is a function of time. 19 . The method as claimed in claim 14 , wherein the EOC is one of a network function or a logical entity within a network function. 20 . The method as claimed in claim 14 , further comprising: updating, a network repository function, the plurality of microservices of the plurality of network function instances. 21 . The method as claimed in claim 14 , wherein the threshold is at least one of pre-defined in standards or configured by the network or could be shared using any network message. 22 . The method as claimed in claim 14 , wherein at least one parameter comprises energy consumption of at least one of at least one microservice, source of energy, load and other energy characteristics. 23 . A method of optimizing energy utilization in a service-based architecture (SBA) based wireless network, the method comprising: receiving, by an energy optimization controller (EOC), power consumed by each of a network function instance of plurality of network function instances, wherein the network function instance comprises plurality of microservices; classifying by the EOC, the plurality of network function instances into at least one first network function instance and at least one second network function instance, wherein the first network function instance comprises at least one network function instance with the power consumed above a threshold and the second network function instance comprises a remaining network function instances; obtaining, by the EOC, energy information comprising information related to power consumed by the plurality of microservices of the at least one first network function instance; selecting, by the EOC, a first at least one microservices from the plurality of microservices of the at least one first network function instance, based on at least one parameter; determining, by the EOC, a second at least one microservice from the first at least one microservice, such that the power consumed by the first network function and the second network function instance is less than a threshold assuming at least one microservice from that first at least one micro service is shifted to the second network function instance; and shifting the second at least one microservice to the at least one second network function instance. 24 . The method as claimed in claim 23 , wherein the network function instance is of a network function type. 25 . The method as claimed in claim 23 , wherein the EOC is one of a network function or a logical entity within a network function. 26 . The method as claimed in claim 23 , further comprising: updating, a network repository function, the plurality of microservices of the plurality of network function instances. 27 . The method as claimed in claim 23 , wherein the threshold is at least one of pre-defined in standards or configured by the network or could be shared using any network message. 28 . The method as claimed in claim 23 , wherein at least one parameter comprises energy consumption of at least one of at least one microservice, source of energy, load and other energy characteristics. 29 . A node for optimizing energy utilization in a service-based architecture (SBA) based wireless network, wherein the node implements an energy optimization controller (EOC), and is configured to: receive, by the EOC, a first power consumption information of a network function instance, wherein the first power consumption is the power consumed by the network function instance; determine, by the EOC, if the first power consumption is above a first threshold; obtain, by the EOC, energy information of plurality of microservices of the network function instance, wherein the energy information comprises information related to power consumed by the plurality of microservices; classify, by the EOC, each of the plurality of microservices based on the received energy information as one of: a high energy utilized microservice, a medium energy utilized microservice, and a low energy utilized microservice; retrieve, by the EOC, at least one microservice classified as the low energy utilized microservice; classify, by the EOC, at least one low energy utilized microservice based on priority level, wherein the priority level is one of: a low priority, and a high priority; identify, by the EOC, at least one low priority microservices; select, by the EOC, at least one microservice of interest; inform by the EOC, at least one microservice of interest to the network function instance; and change, by the network function instance, an operating status of the at least one microservice of interest in the network function instances to de-active. 30 . The node as claimed in claim 29 , wherein the EOC is one of a network function or a logical entity within a netw

Assignees

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Classifications

  • H04L41/08Primary

    Configuration management of networks or network elements (address allocation H04L61/50) · CPC title

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What does patent US2026046198A1 cover?
The evolution of mobile networks marks a significant leap in communication technologies, driven by the demand for high data rates, ultra-low latency, and enhanced connectivity. A key enabler in 5G is the adoption of Micro Service Based Architecture. Microservice Based Architecture decomposes the complex functionality of 5G Core Network into smaller Network Functions (NFs) that are microservice-…
Who is the assignee on this patent?
Centre Of Excellence In Wireless Tech, Indian Inst Tech Madras
What technology area does this patent fall under?
Primary CPC classification H04L41/08. Mapped technology areas include Electricity.
When was this patent published?
Publication date Thu Feb 12 2026 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).