Multi-Cloud Broker Mechanism for Cost Disclosure
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Solution Overview
Problem
Establishing a multi-cloud environment is hindered by direct economic losses for both cloud providers and buyers, leading to a lack of incentive for parties to disclose confidential information technology costs, thereby preventing the establishment of a beneficial multi-cloud environment.
Innovation Solution
A computer-implemented method using a game theoretic model to create a multi-cloud environment, where a probability distribution over information technology costs is established, and a mechanism (centralized broker) collects payments from cloud buyers and makes payments to cloud providers, ensuring truthful participation and maximizing utilities for all parties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a multi-cloud environment is established without a game theoretic mechanism, then cloud providers and buyers can access multiple cloud platforms, but direct economic losses occur for both parties and there is lack of incentive for truthful information disclosure
Solution Approach 1:
The patent introduces a centralized broker as an intermediary mechanism that coordinates transactions between cloud providers and cloud buyers. The broker collects payments from buyers and distributes them to providers based on game theoretic calculations, ensuring that all parties achieve higher utilities than in single-cloud environments. This intermediary structure resolves the economic losses by optimizing resource allocation and payment distribution across the multi-cloud ecosystem.
Solution Approach 2:
The patent transforms the multi-cloud establishment problem by changing the parameters of information disclosure and payment structure. Instead of direct transactions where parties hide their true costs and valuations, the mechanism requires truthful disclosure as a parameter input to the game theoretic model. This parameter change enables the calculation of optimal payments that ensure beneficial outcomes for all participants.
2Loss of information
If cloud parties are incentivized to disclose confidential information technology costs, then optimal payments can be calculated to benefit all parties, but parties initially lack motivation to reveal confidential information
Solution Approach 1:
The patent implements a feedback mechanism where the centralized broker provides truthful disclosure of costs and valuations from all parties back to the respective cloud providers and buyers. This feedback enables each party to see the complete information set, allowing the broker to calculate optimal payments that reflect the true value and cost structure. The feedback loop transforms confidential information into a shared resource that benefits all participants through optimized payment distribution.
Solution Approach 2:
The patent creates equipotentiality by ensuring that all parties achieve equal or higher utility levels compared to single-cloud environments. The game theoretic mechanism calculates payments that balance the interests of providers and buyers, making truthful information disclosure equally beneficial for all parties rather than creating winners and losers. This equipotential outcome removes the harmful lack of incentive by making disclosure advantageous for everyone.
3Productivity
If a centralized broker mechanism is created to collect and distribute payments based on game theoretic models, then utilities for all parties are maximized, but the mechanism and modeling process become more complex
Solution Approach 1:
The patent segments the complex multi-cloud transaction system into distinct functional components: the centralized broker, the game theoretic modeling module, the payment calculation engine, and the information collection interface. This segmentation allows each component to perform its specific function independently, making the overall complex system manageable and implementable. The broker acts as a separate entity that coordinates transactions without requiring direct complex interactions between all providers and buyers.
Data Source
AI summary
Described are techniques for establishing a multi-cloud environment. A multi-cloud environment is modeled using a game theoretic model. Furthermore, a probability distribution over information technology costs for both the cloud buyers and cloud providers is created. Additionally, an estimate of the expected utility (measure of how much benefit a party receives or is expected to receive) for each party in a single-cloud environment is calculated. A mechanism (centralized broker) for the multi-cloud environment is then created that collects payments from the cloud buyers and makes payments to the cloud providers using the expected utility for each party in the single-cloud environment and the probability distribution over information technology costs for both the cloud buyers and the cloud providers as parameters for the game theoretic model, such as by applying an automated mechanism design approach to the game theoretic model.