Utilization Entropy Calculation for Optical Network Fragmentation
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Solution Overview
Problem
Optical communication networks face challenges in determining when fragmentation occurs, making it difficult to identify when network optimization is necessary, as existing techniques lack effective methods to measure the degree of fragmentation and determine when resources need to be dynamically allocated.
Innovation Solution
A system and method for monitoring traffic in networks by calculating utilization entropy values based on the difference in usage status between neighboring slots or links, allowing for statistical analysis to determine link, slot, and path utilization entropy values, which indicate the level of fragmentation and inform optimization decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dynamic resource allocation is implemented in optical networks, then network adaptability improves, but the ability to accurately measure and detect fragmentation levels deteriorates
Solution Approach 1:
The patent transforms the abstract concept of network fragmentation into a measurable parameter by calculating entropy values based on slot usage patterns. By monitoring the distribution and randomness of slot allocations across multiple time periods, the system converts qualitative fragmentation states into quantitative entropy metrics that can be thresholded and acted upon.
Solution Approach 2:
The patent introduces entropy calculation as an intermediary mechanism between resource allocation actions and fragmentation detection. Rather than directly observing fragmentation, the system uses entropy values derived from slot usage patterns as a mediator to indirectly measure the degree of fragmentation and trigger optimization when thresholds are exceeded.
2Productivity
If network optimization is performed frequently, then resource allocation efficiency improves, but network stability deteriorates due to excessive reconfiguration
Solution Approach 1:
The patent implements a feedback mechanism where entropy values are continuously monitored and compared against predefined thresholds. Optimization actions are triggered only when entropy exceeds the threshold, creating a responsive feedback loop that balances resource efficiency with network stability by avoiding unnecessary reconfigurations during normal operating conditions.
Solution Approach 2:
The patent introduces dynamic thresholding and time-based entropy comparison to determine when optimization is warranted. By analyzing entropy changes over multiple time periods and comparing against adaptive thresholds, the system dynamically adjusts optimization timing to balance efficiency gains with network stability requirements.
Data Source
AI summary
A system and method are provided for monitoring traffic in a network comprising a plurality of links, wherein each of the plurality of links comprises a plurality of neighboring pairs of slots. The system and method may include identifying a first usage status and a second usage status, calculating a utilization entropy value based at least on the difference between the first and second usage status, iteratively calculating a set of utilization entropy values for a portion of the network, and calculating an overall utilization entropy value for the portion of the network under analysis based at least on a statistical analysis of the set of utilization entropy values.