Tr 069 Auto Configuration Server – Friendly ACS Server (Automatic Configuration Server), modems, routers, IPTV, STB, ATA, VoIP, storage devices, media centers, IP phones, cameras, etc. A remote control engine for CPE devices such as A user-friendly unified device management platform We provide a single interface to manage ACS and automate the deployment and support of data, voice and video services, improving customer satisfaction and reducing operational and support costs. An easy-to-use user interface covers the entire service lifecycle, from centralized provisioning of remote services to inventory management, batch updates, campaign management, monitoring, event triggering and automation support.
Adding a new device is a challenge for service providers. With its unique Smart Layer technology, Friendly eliminates the need for costly development and integration efforts when adding new types of devices. This feature will significantly reduce total cost of ownership (TCO) by eliminating the need for deep learning of the device management protocol, complex scripting, and integration with OSS and other systems. All the different devices are managed centrally through a management portal.
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In addition to the Subscriber Gateway, the Management Gateway can manage multiple devices from one user, such as VoIP devices, IP phones, STBs, media centers, storage devices, cameras and other devices supported by the TR-111. located behind a NAT.
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The management portal allows you to identify and configure a specific CPE. The system can fully manage the CPE data model, reset or reset the device to factory default settings, upload or download backups, and resolve subscriber issues easily and efficiently.
The management portal allows remote configuration of a group of devices (bulk update). Updates can include parameter values, configuration or firmware files and can be sent to:
The system allows you to download CPE software/firmware image files. The protocol provides mechanisms for versioning, file downloads (ACS-initiated downloads), and reporting the success or failure of file downloads to ACS. A software update can be sent to a single CPE or a group of CPEs. For security purposes, the file may be digitally signed. This signed packet format ensures the integrity of downloaded files and prevents third parties from remotely configuring the device.
During the initial provisioning process, the CPE automatically detects the ACS, registers it, and obtains a default configuration profile with the required policy. The CPE management policy can be updated remotely through the global update process.
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Friendly Technologies is a contributing member of the Broadband Forum’s Broadband User Services Group and is actively involved in the TR-069 standardization process. The TR-069 friendly device management platform supports the following broadband forum technical reports. Support for additional protocols is added as protocols are updated by the Broadband Forum.
The management console continuously provides comprehensive reports on all activities. All reports can be generated from the ACS database through the Management Console or through integration with external platforms such as Business Object. Contact Center Containers Desktop Database and Workflow DevOps Front-end web and mobile development tools
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Telecom service providers (CSPs) often manage millions of customer premises equipment (CPE) devices to provide services to their customers. These devices come in different forms depending on the underlying communication technologies. Cable modems, xDSL modems, set top boxes, and wireless routers are some examples of devices we see in customer environments.
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Many CSPs use the Broadband Forum’s TR-069 protocol (also known as CPE WAN Management Protocol or CWMP) to manage these devices. This protocol enables a single way to manage CPE operations across different types of CPE operations, allowing cloud computing service providers to reuse management levels across different devices through Automatic Configuration Server (ACS) management software. There are many ACS vendors that have successfully implemented the protocol and provide services for CSPs to efficiently manage machine fleets.
Early versions of the TR-069 protocol did not specify a specific method for collecting device telemetry data. In those early days, protocol-defined operations such as GetParameterValues or periodic data were used by ACSs to collect some telemetry data from device agents at regular intervals. However, this method of data collection has led to scalability issues, especially for device fleets containing millions of devices. The Broadband Forum, which saw the issue, introduced a new method of collecting device telemetry data called Aggregate Data Collection and added it to the latest versions of the TR-069 specification.
Aggregate data collection creates a data collection channel external to the device and aims to send telemetry data to an entity other than the ACS. This approach separates concerns and separates configuration management from performance management, allowing functions to grow independently.
Last November, it published TR-069 and its reference architecture, which shows how services can be used to collect telemetry data from devices.
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In this blog post, I’ll explain common CPE telemetry data use cases we see in the industry and outline the TR-069 use cases and the reference architecture that addresses these use cases.
There are some common use cases where CSP telemetry data can be used by CSPs. In this blog post, I’ll explain five use cases and how to solve them using TR-069 bulk data processing as a solution:
In the following sections, I describe these use cases and present a proposed architecture that addresses them.
Real-time dashboards are often cited as the first requirement for data collection projects. These dashboards allow you to display raw or processed data as quickly as possible after rendering. Real-time dashboards allow operations personnel to visualize raw metrics in real-time, display metrics captured to support operations, and troubleshoot issues.
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Heartbeat detection allows cloud computing service providers to locate devices that are not connected to the Internet. This determination can be made in several ways. After aggregate data is collected over HTTPS, a stateful flow analysis program is used to track whether a particular device has sent data within a given time period. Some applications may also use real-time dashboard software to detect missing heartbeats from devices. If aggregate data collection is done via MQTT, device disconnection can be detected immediately because there is a stable connection between the device and the MQTT broker.
Anomaly detection is another use case for processing telemetry data. Certain metrics such as CPU usage, memory usage, or throughput can be used to create a baseline, and the system can generate alerts when current reads deviate from the baseline. Simple threshold checks are also effective for detecting certain anomalies that do not require an ML-based approach. An example of these anomalies is the detection of an increased error rate at the interface.
Once an anomaly is detected, action must be taken to correct it. If an anomaly requires manual action, it is typically sent to an alert or fault map in the CSP’s operational support systems (OSS) for tracking and management. If the error can be resolved automatically (such as restarting the device or changing the Wi-Fi channel), it can be fixed manually. In this setup, the data collection system typically creates a configuration management platform (ACS) to initiate corrective actions on the problem device. Closed-loop automation works in real time.
Effective maintenance aims to fix problems before they occur. For example, for a battery-powered device, regular monitoring of battery voltage levels can identify battery problems before they cause downtime. Effective maintenance analysis typically requires historical rather than real-time data and can be run in batches. Avoiding truck rolls can save CSPs a lot of costs while improving the customer experience.
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Historical accounts are a common example. Historical device data can be used to train machine learning models for the aforementioned ML-based use cases. Another use of this is to solve customer problems. For example, a customer may call the call center and complain about a recurring performance issue that occurs at certain times of the week. Determining the root cause of a customer’s problem is impossible without analyzing historical data. Historical data analysis is also used for research data analysis purposes. Tools often produce hundreds of scales. Determining which ones can be used to solve the aforementioned use cases or to solve new use cases requires studying the available raw data.
To cover the above use cases, the following solution architecture will be used to collect and analyze CPE data. As I mentioned before, this architecture is an implementation of the reference architecture. Depending on the use cases you want to solve, the implementation can be simpler, more complex, or use a different service.
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