Decentralized Data Aggregation via Distributed Ledger
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Solution Overview
Problem
Current data integration solutions face challenges in sharing and auditing state information across computing nodes due to its private nature, leading to difficulties in data collection and aggregation processes, especially when maintaining state information is required throughout the data collection and aggregation task.
Innovation Solution
Implementing a decentralized data collection and aggregation system using a distributed data structure, such as a blockchain, where state information is stored in an immutable and real-time record, allowing for third-party auditing and enabling state information sharing between multiple organizations, including untrusted partners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If state information is kept private to each computing node, then data security and node autonomy are maintained, but data sharing and auditing capabilities are lost
Solution Approach 1:
The system segments state information into two categories: private state data stored locally at each computing node for security, and public state information written to the distributed ledger for sharing. This segmentation allows each node to maintain autonomous control over its sensitive data while contributing verified state changes to the collective system, resolving the contradiction between data security and information sharing
Solution Approach 2:
A distributed ledger acts as an intermediary between private node state and public data sharing. The ledger records immutable audit trails of state changes without exposing raw private data, enabling third-party auditing and multi-organization collaboration while preserving node autonomy and security. This intermediary mechanism resolves the contradiction by providing a trusted mediation layer
2Productivity
If a centralized system collects and aggregates data, then data integration is efficient, but independent auditing and trust verification are compromised
Solution Approach 1:
The centralized data collection function is segmented and distributed across multiple computing nodes, each independently writing to the distributed ledger. This segmentation enables parallel data collection improving efficiency, while the distributed nature of the ledger provides multiple independent audit trails, resolving the contradiction between integration efficiency and auditing reliability
Solution Approach 2:
The distributed ledger provides real-time feedback and verification of state changes across the network. Multiple nodes can independently verify data integrity through the immutable ledger, enabling trustless collaboration. This feedback mechanism maintains auditing capability while allowing efficient parallel data collection, resolving the contradiction
3Adaptability or versatility
If state information is shared across multiple organizations, then collaboration and data integration improve, but system complexity and trust management increase
Solution Approach 1:
The distributed ledger provides universal functionality for all participating organizations, serving as a common trusted infrastructure for data sharing, auditing, and collaboration. This single universal platform replaces complex pairwise trust arrangements, reducing overall system complexity while enabling versatile multi-organization collaboration
Solution Approach 2:
The distributed ledger acts as a neutral intermediary that simplifies trust management among multiple organizations. Instead of each organization needing to establish direct trust relationships with every other participant, the ledger provides a universal mediation layer that enables collaboration while reducing the complexity of trust management
Data Source
AI summary
A computer system performs decentralized collection and aggregation of data. A plurality of requests for data are transmitted, by a data collection server, to a corresponding plurality of remote servers, wherein the plurality of remote server submit responses to the plurality of requests for data to a distributed data structure. The distributed data structure is accessed, by the data collection server, to retrieve the plurality of responses to the plurality of requests. The plurality of responses are aggregated, by the data collection server, into a message and the message is transmitted to an entity requesting data collection. Embodiments of the present invention further include a method and program product for performing decentralized collection and aggregation of data in substantially the same manner described above.