RF Channel Load Balancing Using Long-Term Multi-Filter Analysis
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Solution Overview
Problem
Load balancers in radio frequency communication systems, such as cable modem termination systems, face limitations in processing capabilities, leading to inefficient resource allocation due to challenges in identifying load imbalances and reacting to short-term utilization fluctuations, resulting in non-optimal spectrum resource efficiency.
Innovation Solution
A cloud-based external load balancer that processes extended periods of utilization data, applies multiple filters to identify subsets indicating load imbalances, and reallocates radio frequency resources across computing devices, providing more accurate load balancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If load balancers process extended periods of utilization data, then load balancing accuracy is improved, but processing time and computational resources are increased
Solution Approach 1:
The patent segments the utilization data into multiple time periods and divides the filtering process into multiple stages. The load balancer processes data in manageable chunks rather than handling the entire extended period at once, which maintains accuracy while reducing processing time through systematic data division.
Solution Approach 2:
The patent applies preliminary filtering actions to identify and remove obviously incorrect or irrelevant data points before performing the main load balancing analysis. This preliminary action reduces the amount of data that needs to be processed in detail, maintaining accuracy while reducing processing time.
2Measurement precision
If load balancers apply multiple filters to identify load imbalances, then load balancing accuracy is improved, but device complexity is increased
Solution Approach 1:
The patent segments the filtering process into multiple distinct filters, each targeting specific types of data anomalies or patterns. By dividing the complex filtering task into separate, manageable segments, the system maintains high accuracy through comprehensive filtering while reducing overall processing complexity through modularization.
Solution Approach 2:
The patent applies different filtering criteria to different aspects of the utilization data. Each filter is tailored to address specific local characteristics of the data (such as time-based patterns, threshold violations, or statistical anomalies), which maintains accuracy while reducing complexity by avoiding a single monolithic filtering approach.
3Speed
If load balancers react to short-term utilization fluctuations, then responsiveness is improved, but resource allocation efficiency deteriorates
Solution Approach 1:
The patent applies preliminary filtering to identify and exclude short-term fluctuations from the load balancing decision-making process. By pre-filtering out noisy, short-term data points, the system maintains responsiveness to genuine load changes while avoiding inefficient reactions to temporary fluctuations.
Solution Approach 2:
The patent incorporates feedback mechanisms that evaluate the impact of load balancing decisions before implementing them. This feedback loop allows the system to learn from previous actions and adjust its response to utilization changes, maintaining responsiveness while improving resource allocation efficiency by avoiding counterproductive reactions to short-term fluctuations.
Data Source
AI summary
Methods, devices, and systems for load balancing of radio frequency channels are described herein. A load balancer may receive utilization data for radio frequency channels. The utilization data may span an extended period of time, such as several hours or days. The load balancer may apply multiple filters to the utilization data, where each filter may identify subsets of data that may indicate a load imbalance across the radio frequency channels. The load balancer may select subsets of data that satisfy multiple filters, which may be used for determining a resource allocation for the radio frequency channels. The selection of data satisfying multiple filters, and across a longer period of time, may provide for a more accurate identification of load balance across the radio frequency channels.