EP-4736092-A1 - SYSTEM AND METHOD FOR GOLDEN AUTO CORRECTION FOR MULTI-VENDORS

EP4736092A1EP 4736092 A1EP4736092 A1EP 4736092A1EP-4736092-A1

Abstract

The present disclosure provides a method for generating work orders (WOs) for 5 network nodes. The method allows a processing engine (208) to receive a plurality of parameters from the network nodes. The method uses a work order (WO) module (212) for (i) analyzing the plurality of received parameters to extract a first set of parameters causing discrepancies, (ii) generating one or more WOs based on the extracted first set of parameters and an exclusion list, (iii) 10 executing the generated one or more WOs once it is determined that the one or more WOs belong to the NSA type, and (iv) sending one or more WOs approval requests corresponding to the one or more WOs to a set of approvers if it is determined that the one or more WOs belong to the SA type and executing the one or more WOs within a scheduled time based on the approvals.

Inventors

BHATNAGAR, AAYUSH
BHATNAGAR, PRADEEP KUMAR
SHAH, BRIJESH
CHOURASIA, NITESH KUMAR
TARAN, MAYANK
RISHI, Koul
VIRAG, Patel
DEEPANSHU, Sachdeva
UDAY, Shanbhag

Assignees

Jio Platforms Limited

Dates

Publication Date: 20260506
Application Date: 20240611

Claims (12)

1. A method (1000) for generating work orders (WOs) for network nodes, the method (1000) comprising: receiving (1002), by a processing engine (208), a plurality of parameters from the network nodes; analyzing (1004), by a work order (WO) module (212), the plurality of received parameters to extract a first set of parameters causing one or more discrepancies; receiving (1006), by the WO module (212), an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs; generating (1008), by the WO module (212), the one or more WOs based on the extracted first set of parameters and the received exclusion list; determining (1010), by the WO module (212), whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type; in response to determining that the generated one or more WOs belong to the NSA type, executing (1012), by the WO module (212), the generated one or more WOs; and in response to determining that the generated one or more WOs belong to the SA type, performing (1014), by the WO module (212), following steps: sending (1016) one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers; and executing (1018), in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.
2. The method (1000) as claimed in claim 1, wherein a status of the one or more WOs belonging to the SA type is indicated as expired if they are not approved within a predefined time.
3. The method (1000) as claimed in claim 1, wherein a status of the one or more WOs belonging to the SA type is indicated as expired if the execution of the one or more WOs belonging to the SA type is not completed within the scheduled time.
4. The method (1000) as claimed in claim 2, wherein the predefined time is user configurable.
5. The method (1000) as claimed in claim 1, wherein the plurality of parameters comprise frequency parameters, time division duplex (TDD) frame configuration parameters, link adaptation configuration parameters, network configuration parameters, Signal-to-Noise Ratio (SNR), Signal Quality Index (SQI), and Block Error Rate (BLER), wherein the first set of parameters is a subset of the plurality of parameters, and wherein the exclusion list includes a parameters that are excluded from changes through generation of one or more WOs, and wherein the parameters of the exclusion list comprises the second set of parameters.
6. A system (200) for generating work orders (WOs) for network nodes, the system (200) comprising: a processing engine (208) configured to receive a plurality of parameters from the network nodes, the processing engine (208) comprises: a work order (WO) module (212) configured to analyze the plurality of received parameters to extract a first set of parameters causing one or more discrepancies; the WO module (212) is configured to: receive an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs; generate the one or more WOs based on the extracted first set of parameters and the received exclusion list; determine whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type; in response to determining that the generated one or more WOs belong to the NSA type, execute the generated one or more WOs; in response to determining that the generated one or more WOs belong to the SA type: send one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers; and execute, in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.
7. The system (200) as claimed in claim 6, wherein the system (200) includes an administration module (210) for managing user roles and controlling their access to an execution status of the WOs belonging to the SA type.
8. The system (200) as claimed in claim 6, wherein the administration module (210) allows an administrator to enable or disable a WO creation option, wherein the WO creation option is in a form of a slider.
9. The system (200) as claimed in claim 6, wherein a status of the one or more WOs belonging to the SA type is indicated as expired if they are not approved within a predefined time.
10. The system (200) as claimed in claim 6, wherein a status of the one or more WOs belonging to the SA type is indicated as expired if the execution of the one or more WOs belonging to the SA type is not completed within the scheduled time.
11. A computer program product comprising a non-transitory computer- readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform a method for generating work orders (WOs) for network nodes, the method comprising: receiving, by a processing engine (208), a plurality of parameters from the network nodes; analyzing, by a work order (WO) module (212), the plurality of received parameters to extract a first set of parameters causing one or more discrepancies; receiving, by the WO module (212), an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs; generating, by the WO module (212), the one or more WOs based on the extracted first set of parameters and the received exclusion list; determining, by the WO module (212), whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type; in response to determining that the generated one or more WOs belong to the NSA type, executing, by the WO module (212), the generated one or more WOs; and in response to determining that the generated one or more WOs belong to the SA type, performing, by the WO module (212), following steps: sending one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers; and executing, in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.
12. A user equipment (UE) (104) communicatively coupled with a system (108), the coupling comprises steps of: receiving, by the system (108), a connection request; sending an acknowledgment of the connection request to the UE (104); and transmitting a plurality of signals in response to the connection request to the system (108), wherein the system (108) configured to perform a method (1000) for generating work orders (WOs) for network nodes as claimed in claim 1.

Description

SYSTEM AND METHOD FOR GOLDEN AUTO CORRECTION FOR MULTI-VENDORS RESERVATION OF RIGHTS [0001] A portion of the disclosure of this patent document contains material, which is subject to intellectual property rights such as but are not limited to, copyright, design, trademark, integrated circuit (IC) layout design, and/or trade dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (hereinafter referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully reserved by the owner. TECHNICAL FIELD [0002] The present disclosure relates to the field of network security and infrastructure. More precisely, it relates to a system for a work order module which will extract a list of parameters that are not compliant with particular golden parameter settings defined by network teams and then auto-generate work orders for executing/implementing changes with/without approval. BACKGROUND [0003] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admission of the prior art. [0004] Network discrepancies or blockages can cause a lot of harm to the users such as unwanted latencies, lags, and even corruption of data. Signal degradation refers to a decrease in the quality or strength of a network signal. It can result in issues like dropped calls, poor call quality, or slow data speeds. Signal degradation can be caused by factors such as distance from the cell tower, obstacles blocking the signal, or interference from other electronic devices. Network congestion occurs when there is excessive traffic or high demand on the network infrastructure. This can lead to slower data speeds, increased latency, and delays in data transmission. Network congestion often happens during peak usage times or in densely populated areas. Packet loss happens when data packets being transmitted across the network fail to reach their intended destination. It can occur due to network congestion, faulty network equipment, or issues with the physical transmission medium. Packet loss can result in disruptions to voice calls, video streaming, or data. [0005] Automated systems may occasionally misidentify network discrepancies or generate false alarms, leading to unnecessary corrective actions or overlooking actual issues. This can result in inefficient use of resources and increased operational costs. Automated systems primarily rely on data and algorithms to detect and rectify network discrepancies. However, they may not always have access to contextual information or a comprehensive understanding of the network environment. This can limit their ability to accurately assess the impact of certain issues or make informed decisions on corrective actions. Automated systems are designed based on predefined rules or algorithms. They may struggle to adapt to new or unforeseen network scenarios, emerging technologies, or complex network configurations. This can result in delays or limitations in addressing novel network discrepancies. [0006] While automation can streamline processes, there are instances where human intervention and expertise are still required. Complex network issues or situations that involve multiple factors may necessitate human analysis and decision-making. Over-reliance on automated processes alone may overlook critical nuances or fail to address certain network discrepancies effectively. Automated systems heavily rely on accurate and up-to-date data for effective detection and rectification. If the data is incomplete, inaccurate, or not properly synchronized, it can lead to erroneous decisions and ineffective corrections. Automated processes, if not carefully designed and tested, may inadvertently trigger cascading effects on the network. Incorrect or faulty corrective actions can introduce new issues or worsen existing ones, leading to network instability or degradation. To mitigate these drawbacks, it is important to strike a balance between automated processes and human oversight. Regular monitoring, periodic reviews, and incorporating feedback from network engineers can help refine and improve automated systems, ensuring they are robust, adaptable, and reliable in addressing network discrepancies. [0008] There is, therefore, a need to overcome the above drawbacks and limitations in the current practices to provide a safe and efficient solution for automatically correcting any discrepancies or lags in a given network sy