Network Slice as a Service With Dynamic Equilibrium Pricing
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Solution Overview
Problem
Existing network slice as a service (NSaaS) models lack flexibility and efficiency in pricing and resource allocation, failing to account for market demand and supply dynamics, leading to inefficient resource utilization and unsuitable charging mechanisms.
Innovation Solution
A method and system that utilize a resource and topology-aware NSI valuation approach, involving time-slotted pricing models and auctions, where equilibrium values are determined based on market demand, resource availability, and historical data, with machine learning algorithms optimizing bids to ensure efficient resource allocation and pricing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional charging and policy capabilities are used for NSaaS, then network slice instances can be provided, but the pricing models lack flexibility and cannot account for market demand and supply dynamics
Solution Approach 1:
The patent implements dynamic pricing by determining equilibrium values for network slice instances based on real-time market demand and supply conditions. The system continuously adjusts pricing parameters rather than using fixed traditional charging models, allowing the pricing mechanism to adapt to changing market conditions while maintaining manageable complexity through automated algorithms.
Solution Approach 2:
The system changes pricing parameters dynamically by calculating equilibrium values that reflect current market conditions. Instead of static pricing, the system modifies price parameters based on demand, supply, and time-period variations, enabling flexible pricing that responds to market dynamics without requiring complete redesign of the charging infrastructure.
2Ease of operation
If network slice instances are made readily accessible to enterprise customers, then customer satisfaction improves, but resource utilization efficiency decreases as customers may not fully utilize allocated resources
Solution Approach 1:
The system dynamically allocates network slice instances based on real-time demand assessment. Rather than pre-allocating fixed resources to customers, the system adjusts availability and sizing according to actual usage patterns and market conditions, ensuring resources are accessible when needed while minimizing waste during low-demand periods.
Solution Approach 2:
The equilibrium value calculation incorporates feedback loops that monitor actual resource utilization against allocation. This feedback mechanism allows the system to adjust future allocations based on past usage patterns, rewarding customers who efficiently utilize resources and optimizing overall network resource distribution to reduce unused capacity.
3Productivity
If network providers allocate resources based on fixed pricing models, then resource allocation is simple, but efficiency and revenue optimization are compromised
Solution Approach 1:
The patent implements dynamic resource allocation by determining equilibrium values that reflect current market conditions and resource availability. The system continuously adjusts allocation decisions based on updated pricing parameters and demand signals, maximizing resource utilization efficiency and provider revenue through adaptive rather than static allocation mechanisms.
Solution Approach 2:
The system employs automated algorithms that independently determine equilibrium values and make allocation decisions without requiring complex manual intervention. The self-service mechanism uses machine learning and market data to optimize resource allocation automatically, improving efficiency while keeping the operational complexity manageable through automation rather than human decision-making.
Data Source
AI summary
A method includes defining a first specification for a first network slice, determining a first equilibrium value for a first time period for the first network slice offering, receiving a first bid price for the first network slice for the first time period from a first customer, comparing the first equilibrium value to the first bid price; and providing services using the network slice to the customer during the time period in accordance with the first specification and the bid price if the bid price meets or exceeds the equilibrium value.