Wavefront Multiplexing Cloud Data Storage Redundancy
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Solution Overview
Problem
Current data storage technologies, such as RAID, face challenges in balancing redundancy, performance, and cost, particularly in cloud storage where reliability and security are concerns, with existing methods either being costly or complex and lacking in data integrity monitoring without scrutinizing stored data.
Innovation Solution
Wavefront multiplexing (WF muxing) and demultiplexing techniques transform multiple data sets into weighted sums, storing them in multiple locations with built-in redundancy, allowing for secure, efficient data storage and retrieval while monitoring data integrity without examining the data itself, using orthogonal transformations to ensure data privacy and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mirroring is used to provide complete data redundancy, then reliability is improved, but storage space is doubled (50% wasted)
Solution Approach 1:
The patent combines multiple data sets into a single wavefront multiplexed data structure where redundancy is achieved through mathematical transformations rather than physical duplication. Multiple original data sets are merged into weighted combinations that can be reconstructed from fewer stored copies, eliminating the need for separate mirrored copies of each data set.
Solution Approach 2:
The patent applies wavefront multiplexing transformations that change the representation of data from original form to weighted sum form. By transforming data into a different parameter space (using orthogonal matrices or other transformation techniques), the system achieves redundancy with less storage space while maintaining the ability to reconstruct original data sets.
2Reliability
If parity techniques are used to create redundancy among substreams, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent segments data into multiple data sets that are then processed through wavefront multiplexing. Each segment is transformed and combined with others in a systematic way that creates redundancy without requiring complex parity calculation logic for each individual segment.
Solution Approach 2:
The wavefront multiplexing system serves multiple functions simultaneously: it creates redundancy, enables data reconstruction, and provides a unified framework for storing multiple data sets. This multi-functional approach replaces separate parity creation and reconstruction mechanisms with a single versatile transformation system.
3Reliability
If all data substreams are encrypted before storage, then security is improved, but processing time and computational overhead increase
Solution Approach 1:
The patent applies wavefront multiplexing transformations as a preliminary step before storage, creating a structure that inherently protects data while enabling efficient reconstruction. This preliminary transformation establishes both security and redundancy properties upfront, avoiding the need for time-consuming encryption/decryption operations during data access.
Solution Approach 2:
The patent replaces traditional encryption mechanisms with mathematical transformation-based protection. Instead of using cryptographic algorithms that require significant computational resources, the system uses linear algebra operations (matrix multiplications, orthogonal transformations) that are computationally efficient while providing similar security guarantees through the difficulty of inverting the transformations without proper keys.
4Productivity
If data is striped across multiple drives for parallel communication, then performance is improved, but data integrity monitoring becomes more difficult
Solution Approach 1:
The patent incorporates feedback mechanisms where the wavefront multiplexed structure itself provides information about data integrity. The mathematical relationships between transformed data sets serve as built-in checks, allowing the system to verify data integrity by examining the consistency of the multiplexed structure without needing to scrutinize individual stored data sets.
Data Source
AI summary
An apparatus includes N audio receivers positioned in a pre-defined geometry with respect to P audio sources to receive P audio signals from the P audio sources; N data sets coupled to the N audio receivers to sample the received P audio signals into N data streams; a plurality of storage devices coupled to the N data sets to store the N data streams; and a post processor coupled to the plurality of storage devices to generate output signals corresponding to reconstituted P audio signals using a wavefront demultiplexing transformation, wherein N and P are positive integers and N≥P. The post processor has inputs receiving data retrieved from the plurality of storage devices and outputs providing the output signals.