Wireless Network Blockchain Resource Allocation Using Edge Computing
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Solution Overview
Problem
Blockchain technologies, particularly those using Proof of Work (POW) consensus mechanisms, are resource-intensive, requiring high-powered servers that consume significant electrical power and space, making widespread application infeasible.
Innovation Solution
A Blockchain Service Repository Function (BCSRF) within a wireless telecommunication network dynamically allocates blockchain operations across heterogenous computing devices, utilizing machine learning to optimize resource distribution and reduce the need for dedicated high-processing servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high-powered servers are used to perform computationally-intensive blockchain operations, then the reliability and processing capability of the blockchain network is improved, but the cost, electrical power consumption, and space requirements increase significantly
Solution Approach 1:
The patent segments the blockchain network into two functional parts: a lightweight coordination layer (blockchain nodes that maintain the ledger and propose blocks) and a distributed computation layer (edge devices that perform the computationally-intensive operations). This segmentation allows the system to achieve high processing capability through distributed edge computing while avoiding the need for centralized high-powered servers, thereby reducing energy consumption and costs.
Solution Approach 2:
The patent enables edge devices to serve multiple functions: they act as both blockchain participants (performing light validation and consensus) and distributed computing resources (performing computationally-intensive operations). This multi-functionality allows the same devices to contribute to blockchain security while providing processing power, eliminating the need for separate high-powered servers and reducing overall system energy consumption.
2Productivity
If high-powered servers are deployed for blockchain operations, then the processing capability is improved, but the device complexity and infrastructure requirements increase
Solution Approach 1:
The patent divides the blockchain infrastructure into simple coordination nodes and distributed edge devices with varying computational capabilities. This segmentation allows the system to achieve high processing capability through the collective power of many simple devices rather than relying on complex centralized servers, thereby reducing device complexity and infrastructure requirements.
Solution Approach 2:
The patent enables edge devices to autonomously participate in blockchain operations and provide computing resources without requiring centralized management or complex server infrastructure. Devices self-register, self-manage their computational contributions, and self-coordinate through standard blockchain protocols, eliminating the need for complex server deployment and management infrastructure.
3Reliability
If dedicated high-processing servers are used for blockchain operations, then the consensus reliability is improved, but the cost and scalability are worsened
Solution Approach 1:
The patent segments consensus-critical functions (ledger maintenance, block proposal, validation) from computationally-intensive operations. This allows consensus reliability to be maintained by a distributed set of lightweight nodes while scalability is achieved by adding more edge devices for computation. The segmented architecture enables independent scaling of each function without compromising the other.
Solution Approach 2:
The patent creates a dynamic system where the computing resources available for blockchain operations can flexibly expand and contract based on network needs. Edge devices can dynamically join and leave the network, and their computational contributions can be adjusted in real-time, enabling the system to scale adaptively while maintaining consensus reliability through the persistent lightweight coordination layer.
Data Source
AI summary
The disclosed technology relates to utilizing computing resource nodes available to a wireless telecommunications network to distribute performance of blockchain operations throughout the wireless telecommunication network nodes. A wireless telecommunication network includes computing resources across multiple domains, including core network servers, base stations, and user devices. An example wireless telecommunication network includes a network-integrated blockchain service via which a blockchain node can submit a service request for usage of network resources to complete a blockchain operation (e.g., determining a cryptographic hash of data to be added to a blockchain) and via which a service result (e.g., a final hash value) can be returned to the blockchain node. The network-integrated blockchain service uses a machine learning (ML) model to predict and select certain network computing devices with resource availability.