Virtualized PMA Control for Low-Power Remote DPUs and DSLAMs
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Solution Overview
Problem
The increasing computational burdens and resource constraints faced by remotely deployed network components such as DPUs and DSLAMs, exacerbated by size reduction and limited power availability, necessitate more efficient management and virtualization solutions.
Innovation Solution
Implementing virtualization of access node functions and Persistent Management Agent (PMA) functions to centralize and control DPU and DSLAM components, leveraging virtualized computing infrastructure to offload processing from field-deployed devices to data centers, thereby reducing computational and resource demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network components (DPU, DSLAM) are deployed remotely into the field, then network coverage and connectivity are improved, but computational burdens and complexity increase while physical size and power capacity are constrained
Solution Approach 1:
The patent extracts computational functions from the remote network components and relocates them to a centralized cloud platform. The DPU and DSLAM retain only essential local functions for signal processing and customer access, while complex tasks such as traffic management, provisioning, and maintenance are extracted and executed remotely in the cloud, thereby reducing on-site computational complexity.
Solution Approach 2:
The patent introduces a cloud-based management platform as an intermediary between the remote network components and the central network controller. This intermediary handles complex computational tasks, allowing the remote devices to operate with minimal local processing power while maintaining full network functionality through remote management and control.
2Volume of moving object
If physical size of network components is reduced, then installation space requirements decrease, but computational capabilities and processing power become insufficient
Solution Approach 1:
The patent extracts computationally intensive functions from the compact remote devices and relocates them to the cloud. The small form-factor DPU and DSLAM retain only essential signal processing capabilities, while advanced computational tasks are extracted and performed remotely, enabling miniaturization without sacrificing processing power.
Solution Approach 2:
The patent replaces the mechanical/computational processing capacity that would be required within a small physical device with a distributed cloud-based computing system. This substitution allows the physical device to be miniaturized while the cloud infrastructure provides the necessary computational power through network communication.
3Adaptability or versatility
If remote cooling capacity and electrical requirements are constrained, then deployment flexibility improves, but power consumption and thermal management become more difficult
Solution Approach 1:
The patent extracts power-intensive computational functions from the remote devices and relocates them to the cloud. The on-site equipment consumes only minimal power for basic signal processing and communication, while the cloud data center handles the power-intensive tasks such as traffic analysis, encryption, and data processing, thereby enabling deployment in locations with constrained power and cooling capacity.
4Productivity
If access node functions are virtualized, then cost per computation decreases and scalability improves, but management complexity and system configuration become more difficult
Solution Approach 1:
The patent implements a universal cloud-based management platform that handles multiple functions including traffic management, provisioning, maintenance, and monitoring through a single integrated system. This multi-functional approach consolidates management tasks that would otherwise require separate complex systems, thereby reducing overall management complexity while achieving cost efficiency through resource sharing.
Solution Approach 2:
The patent implements self-service capabilities where the cloud platform automatically performs provisioning, configuration, and maintenance tasks without requiring manual intervention at remote locations. The system automatically manages virtual network functions, allocates resources, and performs fault detection, thereby reducing management complexity while achieving high cost efficiency through automation.
Data Source
AI summary
In accordance with embodiments disclosed herein, an exemplary system or computer implemented method for implementing Persistent Management Agent (PMA) functions for the control and coordination of DPU and DSLAM components may include, for example: a memory to store instructions for execution; one or more processors to execute the instructions; a virtualized module operating on virtualized computing infrastructure, in which the virtualized module is to provide a virtualized implementation of a plurality of functions associated with one or more remotely located Distribution Point Units (DPUs) and/or Digital Subscriber Line Access Multiplexers (DSLAMs), each of the one or more remotely located DPUs and/or DSLAMs having a plurality of broadband lines coupled thereto; in which the virtualized module is to further control Persistent Management Agent (PMA) functions and control coordination of the one or more remotely located DPUs and/or DSLAMs and the plurality of broadband lines coupled with the one or more remotely located DPUs and/or DSLAMs by virtualizing one or more functions of the one or more remotely located DPUs and/or DSLAMs to operate on the virtualized computing infrastructure; and a network interface to receive data and send control instructions for operation of the plurality of broadband lines to and from the one or more remotely located DPUs and/or DSLAMs. Other related embodiments are disclosed.