Tokenizing Distributed Compute Resources in Hybrid Fog Clouds
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack an automated platform for real-time metering and tokenization of distributed compute resources in a multi-tenant hybrid fog computing cloud, leading to inaccurate measurement and potential overcharging of compute resources.
Innovation Solution
A system integrating an edge computing platform with collectors, meters, and analytics platforms to monitor and aggregate compute metrics, generate metering data, and develop billing schemes, using serverless functions and distributed ledger technology for real-time tokenization and compensation of compute resources across multiple nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual metering and billing systems are used for distributed compute resources, then system complexity is reduced, but measurement precision and real-time accuracy deteriorate leading to inaccurate resource usage measurement and potential overcharging
Solution Approach 1:
The system segments the distributed compute resources into individual metering units, with each node equipped with its own collector and meter components. This segmentation enables precise measurement at the node level while distributing the complexity across multiple independent units rather than requiring a complex centralized system.
Solution Approach 2:
Each compute node in the distributed system performs self-metering through local collectors that automatically gather resource usage data and meters that calculate consumption metrics. This self-service approach eliminates the need for complex external monitoring systems while achieving high measurement precision through distributed autonomous measurement.
2Productivity
If centralized billing systems are used for multi-tenant hybrid fog computing cloud, then device complexity is reduced, but productivity and real-time processing capability deteriorate leading to increased latency in billing operations
Solution Approach 1:
The billing system is segmented into distributed components across multiple edge computing nodes, with each node capable of independent metering and billing operations. This segmentation enables parallel processing of billing transactions across the network, dramatically improving real-time processing capability while distributing system architecture complexity across nodes rather than concentrating it centrally.
Solution Approach 2:
The system transitions from a single-dimensional centralized billing architecture to a multi-dimensional distributed architecture operating across spatial (multiple nodes) and temporal (real-time continuous processing) dimensions. This dimensional change enables simultaneous billing operations across numerous nodes, achieving high productivity while managing complexity through distributed parallelism.
3Reliability
If distributed ledger technology is integrated for resource compensation, then data integrity and security are improved, but device complexity and implementation difficulty increase
Solution Approach 1:
The distributed ledger implementation uses a universal blockchain protocol that serves multiple functions simultaneously: recording resource usage data, verifying metering accuracy, enabling transparent billing, and facilitating automated compensation. This multi-functionality achieves high data integrity while reducing implementation complexity by using a single standardized protocol rather than multiple specialized systems.
Solution Approach 2:
The blockchain acts as an intermediary layer between the distributed metering nodes and the billing system, providing automated verification and consensus mechanisms. This intermediary simplifies the integration complexity by handling data integrity and security concerns through established blockchain protocols, allowing the metering system to focus on measurement functions while the blockchain handles verification and recording.
Data Source
AI summary
The present invention provides systems and methods for tokenization of distributed compute resources. The distributed compute resources are provided in a multi-tenant hybrid fog computing cloud. The plurality of nodes are organized in a peer-to-peer edge network. The tokenization of distributed compute resources is automated and occurs in real time.