Dynamic Network Capacity Allocation via Shadow Price Indications
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing network capacity management systems fail to optimally allocate resources between different service or traffic classes in packet networks, as they assume fixed capacity allocations and do not effectively utilize congestion prices to maximize value generation.
Innovation Solution
The method and system adaptively adjust network capacity allocations between services or traffic classes based on congestion-influenced 'shadow price indications,' which represent the marginal value of additional capacity, using shadow price functions that consider both traffic rates and allocated capacities to optimize capacity distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed capacity allocations are used for different service classes, then network management is simplified, but resource utilization efficiency and value generation are suboptimal
Solution Approach 1:
The patent implements dynamic capacity allocation by continuously adjusting the capacity assigned to different service classes based on real-time shadow price indications. The system monitors congestion levels and service-specific shadow prices, then dynamically reallocates network capacity to maximize value generation, transforming the static capacity management into an adaptive dynamic system that responds to changing network conditions and service demands.
2Productivity
If capacity is reallocated based on shadow price indications, then value generation is maximized, but system complexity increases
Solution Approach 1:
The patent employs feedback mechanisms where shadow price indications are calculated based on congestion prices and service-specific factors, then fed back into the capacity allocation decision-making process. The system continuously monitors network state, calculates shadow prices for different service classes, and uses this feedback information to adjust capacity allocations, creating a closed-loop control system that adapts to changing conditions while systematically managing complexity through structured feedback processing.
Solution Approach 2:
The patent changes the key parameter of capacity allocation from fixed to variable, driven by shadow price indications that reflect both congestion levels and service-specific characteristics. By introducing shadow price as a controlling parameter and allowing capacity allocations to vary based on this parameter, the system achieves optimized value generation while managing complexity through parameter-driven decision rules rather than complex heuristic algorithms.
3Ease of operation
If congestion prices are used for traffic management, then traffic control within service classes improves, but capacity allocation between service classes remains suboptimal
Solution Approach 1:
The patent merges two previously separate functions: congestion-based traffic control within service classes and capacity allocation between service classes. By combining congestion prices with service-specific shadow price indications, the system creates a unified capacity management framework that simultaneously optimizes both intra-class traffic control and inter-class capacity allocation, eliminating the suboptimality that arose when these functions were handled separately.
Data Source
AI summary
A method and system is described that adjusts the allocated capacity of a network between services, or service or traffic classes, in dependence on a congestion-influenced shadow price indication in respect of each service or class. In this respect, instead of viewing the congestion price as a cost of using already allocated unit of capacity, such a shadow price indication can be viewed as an indicator of the value obtainable from allocating an extra unit of capacity to a service or class. By so doing the shadow price indication becomes a factor to be taken into account in deciding on capacity allocation between services or classes, with a high shadow price indication for a service or class indicating that additional value would likely be obtained by allocating an additional unit of capacity to the service or class.