Hierarchical Computing Network Scaling Reliability
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Solution Overview
Problem
Current Cloud computing architectures face issues with service reliability, data security, and scalability due to centralization, leading to single points of failure, high costs, and latency problems, especially as demand for uptime and storage increases.
Innovation Solution
A hierarchical computing network is proposed, where multiple service nodes are organized into layers with redundancy, allowing for linear scaling of uptime by adding or removing nodes, and incentivizing participants to share spare capacity by rewarding uptime and penalizing downtime, enabling end-users to choose service levels based on reliability and cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud services are provided from a few large-scale data centers, then service coverage and capacity are improved, but service reliability deteriorates due to single points of failure
Solution Approach 1:
The patent segments the centralized cloud service into multiple distributed service nodes organized in a hierarchical network structure. Each node operates independently, eliminating single points of failure while maintaining collective service capacity. The segmentation allows the system to scale by adding more nodes without compromising reliability.
Solution Approach 2:
The patent changes the architectural parameter from centralized to distributed hierarchical structure. This parameter change enables the system to achieve both high capacity (through multiple nodes) and high reliability (through redundancy and failover capabilities at each hierarchical level).
2Reliability
If more service nodes are added to increase reliability, then service uptime is improved, but system complexity increases
Solution Approach 1:
The hierarchical segmentation of service nodes into multiple levels (edge nodes, regional nodes, global nodes) organizes complexity in a structured manner. Each level manages a specific scope of services, making the overall system more manageable despite the large number of nodes.
Solution Approach 2:
The patent introduces a hierarchical dimension to organize service nodes vertically rather than horizontally. This dimensional change transforms the complexity management from flat peer-to-peer relationships to structured hierarchical relationships, reducing the operational complexity despite increased node count.
3Loss of energy
If personal computers are utilized for cloud services, then infrastructure cost is reduced, but service reliability deteriorates due to hardware limitations
Solution Approach 1:
The patent merges multiple personal computers into a collective hierarchical network where individual hardware limitations are compensated by the aggregate capacity and redundancy of the entire network. The combination transforms weak individual nodes into a robust distributed system.
Solution Approach 2:
The patent implements data and service copying across multiple personal computer nodes at different hierarchical levels. This copying strategy ensures that service availability is maintained even if individual nodes fail, compensating for hardware reliability limitations through redundancy.
Data Source
AI summary
The present invention provides a method of scaling the reliability of the service of a hierarchical computing network with large number of participant nodes servicing large number of users with large volume of data by adding/subtracting a service node to/from a service node group to linearly increase/decrease the network service uptime. Also disclosed is a method of incentivizing the owner of a participant computer in a general computer network to continuously and reliably share its spare capacity and capability by rewarding/punishing the participant computer with increased/decreased uptime value if a fault incident of the participant computer is/is not detected; and making the uptime value of the participant computer visible to end users.