Location-Constrained Data Storage for Compliant Distributed Analytics
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Solution Overview
Problem
Existing data storage and analytics systems fail to enforce location constraints, which are mandated by regulations for data privacy and security, leading to inefficiencies and compliance challenges for multinational organizations.
Innovation Solution
A data storage and analytics service (DSAS) that implements programmatic interfaces to manage location constraints, replicates data subsets proactively, and performs location-aware computations to ensure compliance with regulatory requirements, while minimizing network bandwidth and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored in centralized repositories for efficient analysis, then analysis efficiency is improved, but location constraint compliance deteriorates
Solution Approach 1:
The patent segments data into partitions with different location constraints and applies different replication strategies to each partition. Location-constrained partitions are kept in specific regions, while location-unconstrained partitions are replicated across regions for efficient analysis, resolving the contradiction between centralized analysis efficiency and location constraint compliance.
Solution Approach 2:
The patent applies different quality characteristics to different parts of the data system. Location-constrained data partitions maintain strict location adherence, while location-unconstrained partitions enable cross-region replication and distributed analysis, allowing the system to optimize for both compliance and efficiency in different contexts.
2Reliability
If data is replicated across multiple locations for compliance, then location constraint compliance is improved, but network bandwidth usage deteriorates
Solution Approach 1:
The patent applies partial replication only to location-unconstrained data partitions rather than replicating all data. This selective approach ensures compliance for constrained data while minimizing unnecessary network bandwidth consumption for unconstrained data, reducing overall energy loss.
Solution Approach 2:
The patent extracts and identifies location-unconstrained data partitions from the overall dataset, applying optimized replication only to these portions. This separation allows the system to minimize network bandwidth usage by avoiding replication of data that doesn't require it, while still ensuring compliance for constrained data.
3Ease of operation
If location-constrained data is accessed from remote locations, then data accessibility is improved, but compliance with location regulations deteriorates
Solution Approach 1:
The patent segments data access permissions based on location constraints. Location-constrained partitions are accessible only from authorized regions, while location-unconstrained partitions enable cross-region access. This segmentation maintains regulatory compliance for sensitive data while providing accessibility where permitted.
Solution Approach 2:
The patent introduces a location-aware data access layer that mediates between user access requests and physical data storage locations. This intermediary enforces location constraints by routing access requests appropriately, ensuring compliance while maintaining accessibility for authorized users regardless of their physical location.
Data Source
AI summary
A constraint on a location at which a portion of a data set can be stored is determined based on input received via a programmatic interface. The portion of the data set is stored at a location selected in accordance with the constraint. An analysis operation, whose input includes the portion of the data set, is performed at a set of computing resources selected from a plurality of resources based at least in part on their location.