Multiplexer Grooming Optimization via Channel Assignment
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Solution Overview
Problem
Communication network multiplexers are inefficiently utilized due to challenges in determining optimal data throughput and modifying network assets in response to changes in customer base, leading to high costs and operational inefficiencies in grooming processes.
Innovation Solution
A system and method for optimizing multiplexer configurations by determining an optimization value for each configuration, identifying the highest-ranked configuration, and employing it to optimize multiplexer utilization, which includes a multiplexer configuration access module, optimizer, service delivery point clustering, discrete event simulation, and network visualization to minimize costs and maximize efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiplexer configurations are frequently modified in response to customer base changes, then network service efficiency is improved, but operational costs (labor, planning, termination fees) increase
Solution Approach 1:
The system performs preliminary analysis of customer base changes and multiplexer configurations before actual reconfiguration occurs. By predicting future traffic patterns and pre-planning optimal configurations, the system minimizes reactive changes and reduces the frequency of costly reconfigurations while maintaining network efficiency.
Solution Approach 2:
The system continuously monitors network traffic patterns, customer base changes, and multiplexer performance metrics. This feedback loop enables the system to identify when reconfiguration is truly necessary versus when current configurations remain optimal, thereby reducing unnecessary operational changes and associated costs.
2Loss of energy
If the number of multiplexers is reduced to lower costs, then operational expenses decrease, but network capacity and service quality may deteriorate
Solution Approach 1:
The system analyzes multiple configuration parameters simultaneously (traffic volume, channel assignments, multiplexer utilization rates, geographic distribution) to identify optimal configurations that maintain network capacity while reducing the number of active multiplexers. By changing parameters in coordinated ways rather than isolated adjustments, the system achieves cost reduction without compromising service quality.
Solution Approach 2:
The system identifies opportunities to consolidate traffic from multiple multiplexers into fewer units by optimizing routing and channel assignments. Existing multiplexers are utilized more fully to handle diverse traffic types and geographic regions, making them multi-functional and reducing the need for dedicated multiplexers for specific purposes.
3Productivity
If data channels are reallocated from one multiplexer to another, then multiplexer utilization efficiency is improved, but reconfiguration costs (movement costs, mileage) increase
Solution Approach 1:
The system implements partial reconfigurations rather than complete reallocations. By making targeted adjustments to specific data channels that provide the greatest utilization improvement, versus complete reconfiguration of all channels, the system achieves efficiency gains while minimizing movement costs and operational disruptions.
Data Source
AI summary
Aspects of optimized grooming of multiplexers of a communication network are presented. In an example method, an optimization value associated with each of a plurality of multiplexer configurations may be determined, wherein each of the plurality of multiplexer configurations includes a proposed assignment of each of a plurality of data channels to one of a plurality of inputs of a plurality of multiplexers. A multiplexer configuration having a highest-ranked optimization value of the plurality of multiplexer configurations may be identified and subsequently used to configure the multiplexers. Other potential aspects of the present disclosure are described in greater detail below.