Token-Based Billing for Load-Adaptive Server-Side Rendering
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Solution Overview
Problem
Existing server-side rendering technologies face challenges in managing resource allocation and billing for delivering high-demand applications, such as video games, without requiring users to invest in high-end hardware, and there is a need for a flexible and dynamic billing model that adapts to varying loads and user demands.
Innovation Solution
A token-based billing model where each user is associated with tokens representing access rights, with expiration rates adjusted based on aggregate and individual load, allowing users to adjust session quality parameters to manage token expiration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If server-side rendering is used to deliver high-demand applications without requiring users to invest in high-end hardware, then accessibility and ease of operation are improved, but resource allocation management and billing complexity increase
Solution Approach 1:
The patent segments the billing model into discrete tokens that represent individual units of access time. Each token is a separate, manageable entity that can be independently tracked, allocated, and expired. This segmentation simplifies the overall billing complexity by breaking down the continuous resource allocation problem into discrete, countable units.
Solution Approach 2:
The patent implements dynamic token expiration rates that adjust based on aggregate system load and individual user loads. The expiration rate is not fixed but changes dynamically to reflect current resource availability and demand conditions. This dynamic approach allows the system to automatically balance accessibility with resource management without requiring complex manual intervention.
2Ease of manufacture
If a fixed token expiration rate is used, then billing simplicity is improved, but adaptability to varying loads and user demands deteriorates
Solution Approach 1:
The patent transforms the static token expiration rate into a dynamic parameter that automatically adjusts based on system conditions. The expiration rate responds to aggregate load across all users and individual user loads, enabling the billing model to adapt to varying demands while maintaining its token-based structure. This resolves the contradiction by making the system both simple in structure and adaptive in behavior.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors aggregate load and individual user loads, then uses this information to adjust token expiration rates. The feedback loop ensures that the billing model adapts to current conditions without requiring manual reconfiguration, maintaining simplicity while achieving adaptability.
3Productivity
If tokens are allocated without considering individual user loads, then allocation speed is improved, but fairness and resource optimization deteriorate
Solution Approach 1:
The patent implements feedback-based token expiration where individual user loads are monitored and fed back into the expiration rate calculation. Each user's token expiration is adjusted based on their specific resource consumption patterns, ensuring that users who consume more resources have their tokens expire faster, thereby maintaining fairness while preserving automatic adjustment capabilities.
Solution Approach 2:
The patent applies different expiration rates to different users based on their individual load characteristics. Rather than applying a uniform expiration rate to all users, the system tailors the expiration rate to each user's specific resource consumption, ensuring local optimization and fairness for each user while maintaining overall system efficiency.
Data Source
AI summary
A token-based billing model for delivering server-side rendered applications to remote users. A token represents a right to access a server-side rendered application. Each remote user is associated with one or more tokens. When a given token expires, the set of tokens associated with a user is decremented. The rate at which tokens expire are modulated based on aggregate load across the resources of the server-side rendered application provider, as well as the individual loads attributable to each of the users.