REAL-TIME INVENTORY FOR CLOUD NETWORK RESOURCES
A cellular network having radio access network (RAN) nodes where each RAN node includes (i) a central unit (CU) that resides on a public cloud of the cellular network, (ii) a distributed unit (DU) that resides on a private cloud of the cellular network such that the DU is in communication with the CU on the public cloud of the cellular network, and (iii) a radio unit (RU) under control of the DU. The cellular network also has network repository functions (NRFs) that are distributed on the cellular network and reside on at least the public cloud of the cellular network where the NRFs control operation of cell sites and local data centers (LDCs) on the cellular network. The network also has processors configured to control data collection edge applications residing with the NRFs that are distributed on the cellular network.
1 . A network repository function (NRF) distributed on a cellular network, the NRF residing on at least a public cloud of a cellular network, comprising:
one or more processors configured to:
control operation of at least one cell site or at least one local data center;
receive one or more messages from a data collection edge application associated with the NRF; and
transmit operating data to the data collection edge application based on the one or more messages.
2 . The NRF of claim 1 , wherein the NRF resides on a public cloud of the cellular network.
3 . The NRF of claim 1 , wherein the one or more processors are configured to:
control the operation of at least one cell site and at least one local data center of the cellular network.
4 . The NRF of claim 1 , wherein to transmit the operating data, the one or more processors are further configured to:
identify operating data of one or more cell sites associated with the NRF based on the one or more messages received from the data collection edge application; and
transmit the operating data of the one or more cell sites to the data collection edge application.
5 . The NRF of claim 1 , wherein the one or more processors are further configured to:
cause an artificial intelligence cellular communication management program controlling one or more RAN nodes adjusts its operational parameters using machine learning based on at least a portion of the operating data transmitted by the NRF.
6 . The NRF of claim 1 , wherein the processors are configured to:
receive one or more messages from a data collection edge application that indicate that a new user plane function has registered to the NRF;
obtain operating data associated with the new user plane function; and
transmit the operating data associated with the new user plane function to the data collection edge application.
7 . A method of operating a data collection edge application, the method comprising:
sending a message to a network repository function (NRF) associated with a cellular network, the NRF residing on at least a public cloud of the cellular network and being configured to control operation of at least one cell site or at least one data center;
receiving a response from the NRF, the response including operating data of the NRF;
filtering the operating data to obtain filtered operating data;
formatting the filtered operating data to obtain formatted operating data; and
causing the formatted operating data to be used to track resource inventory on the cellular network.
8 . The method of claim 7 , wherein causing the formatted operating data to be used to track resource inventory on the cellular network comprises:
transmitting the formatted operating data to at least one data collection tracking agent configured to track resource inventory on the cellular network based on formatted operating data.
9 . The method of claim 7 , wherein the filtering includes removing duplicative information from the operating data.
10 . The method of claim 7 , wherein the filtering further includes:
determining if any of the operating data is immaterial based on a predetermined classification; and
removing the immaterial operating data.
11 . The method of claim 7 , wherein an artificial intelligence cellular communication management program controlling one or more RAN nodes of the cellular network adjusts its operational parameters using machine learning based on the resource inventory.
12 . The method of claim 7 , further comprising:
detecting that a new cellular network function has registered to the NRF;
sending a message to the NRF requesting operating data associated with the new cellular network function; and
receiving operating data associated with the new cellular network function from the NRF.
13 . The method of claim 7 , further comprising:
detecting that a response has not been received from the NRF after a threshold period of time; and
transmit an indication to a data collection edge tracking agent that a response has not been received from the NRF after the threshold period of time.
14 . A nontransitory processor-readable storage medium that stores at least one of instructions or data, the instructions or data, when executed by at least one processor, cause the at least one processor to perform a method comprising:
send a message to a network repository function (NRF) associated with a cellular network, the NRF residing on at least a public cloud of the cellular network and being configured to control operation of at least one cell site or at least one data center;
receive a response from the NRF, the response including operating data of the NRF;
filter the operating data to obtain filtered operating data;
format the filtered operating data to obtain formatted operating data; and
cause the formatted operating data to be used to track resource inventory on the cellular network.
15 . The nontransitory processor-readable storage medium of claim 14 , wherein, to cause the formatted operating data to be used to track resource inventory on the cellular network, the instructions or data further cause the at least one processor to:
transmit the formatted operating data to at least one data collection tracking agent configured to track resource inventory on the cellular network based on formatted operating data.
16 . The nontransitory processor-readable storage medium of claim 14 , wherein, to filter the formatted operating data, the instructions or data further cause the at least one processor to remove duplicative information from the operating data.
17 . The nontransitory processor-readable storage medium of claim 14 , wherein, to filter the formatted operating data, the instructions or data further cause the at least one processor to:
determine if any of the operating data is immaterial based on a predetermined classification; and
remove the immaterial operating data.
18 . The nontransitory processor-readable storage medium of claim 14 , wherein an artificial intelligence cellular communication management program controlling one or more RAN nodes of the cellular network adjusts its operational parameters using machine learning based on the resource inventory.
19 . The nontransitory processor-readable storage medium of claim 14 , wherein the instructions or data further cause the at least one processor to:
detect that a new cellular network function has registered to the NRF;
send a message to the NRF requesting operating data associated with the new cellular network function; and
receive operating data associated with the new cellular network function from the NRF.
20 . The nontransitory processor-readable storage medium of claim 14 , wherein the instructions or data further cause the at least one processor to:
detect that a response has not been received from the NRF after a threshold period of time; and
transmit an indication to a data collection edge tracking agent that a response has not been received from the NRF after the threshold period of time.