Value-Density Data Transmission Selection Under Capacity Constraints
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Solution Overview
Problem
Data communication networks face challenges in managing data transmission requests that exceed the capabilities of communication pathways, leading to unmet demands and inefficiencies in resource utilization.
Innovation Solution
A method and system for optimizing data transmission by selecting requests based on value densities and constraints, using techniques such as maximum-value-density optimization and maximum-value optimization to determine which requests to accept, ensuring that data transmission constraints are not exceeded while maximizing value or priority.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If all data transmission requests are accepted, then the demand of end nodes is fully met, but the communication pathway constraints are exceeded
Solution Approach 1:
The patent changes the selection parameter from simple first-come-first-served to value density (value/demand ratio), allowing the system to prioritize requests that provide maximum value per unit of resource consumed, thus optimizing capacity utilization while maintaining constraint satisfaction
Solution Approach 2:
The patent applies different selection criteria to different requests based on their individual value and demand characteristics, rather than applying a uniform acceptance policy to all requests
2Productivity
If optimal request selection is performed to maximize value, then the value density is maximized, but the computational complexity increases
Solution Approach 1:
The system automatically performs value density calculations and request selection without requiring external intervention or complex manual optimization processes, making the computational task self-contained and manageable
Solution Approach 2:
The patent transforms the complex optimization problem into a simpler ratio-based selection process by using value density as the key parameter, reducing computational complexity while maintaining optimization effectiveness
3Productivity
If requests are selected based on highest value density, then the aggregate value is maximized, but the residual space in communication pathway is increased
Solution Approach 1:
The patent accepts that some residual space will remain after optimization, treating this as an acceptable partial outcome rather than attempting to eliminate all residual space, which would require excessive computational effort
Data Source
AI summary
A method for managing data transmissions includes: receiving data transmission requests; and determining which requests to accept such that a constraint of a network communication pathway is not exceeded, by: selecting a set of requests based on value densities, determining a first non-selected request that doesn't exceed a residual amount, determining whether a second non-selected request exists for which: (1) its value density is greater than a combined value density of the first non-selected request and a request of the selected requests that has a lowest value density, and (2) its demand is the largest among non-selected requests meeting requirement (1) that is no larger than a sum of the residual amount and a demand of a lowest value density selected request, and if it exists, replacing the lowest value density selected request with the second non-selected request and, if not, include the first non-selected request as a selected request.