Distributed Cloud Storage Allocation Across Disparate Endpoint Devices
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Solution Overview
Problem
Current technologies face challenges in efficiently utilizing endpoint devices for data storage due to variations in processing capabilities, network latencies, mobility, and uptime, leading to inefficiencies in data availability and reliability within networked systems.
Innovation Solution
A system that allocates unused storage space on endpoint devices to create a distributed cloud data repository, using a centralized data management system to index and divide data into chunks, encrypt them, and store them across multiple devices based on processing power, bandwidth, and uptime, with a machine learning component to dynamically adjust redundancy and storage configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is stored on multiple disparate endpoint devices with different processing capabilities and uptimes, then storage capacity and data availability are improved, but data reliability and accessibility deteriorate due to variations in device performance and online status
Solution Approach 1:
The patent segments cloud data into multiple encrypted chunks and distributes them across different endpoint devices. Each device stores only a portion of the data, and the system maintains a mapping between data identifiers and device identifiers to enable reliable retrieval by reconstructing the original data from the distributed chunks.
Solution Approach 2:
The system dynamically adjusts the number of data chunks and their distribution across devices based on device attributes such as processing power, bandwidth capability, and uptime. This parameter adaptation ensures that data reliability is maintained while utilizing the heterogeneous capabilities of disparate endpoint devices.
2Quantity of substance
If data is distributed across multiple endpoint devices, then storage scalability is improved, but system complexity increases due to data management, distribution, and retrieval coordination
Solution Approach 1:
The patent introduces a centralized system comprising a data management component and a data packing component that act as intermediaries between the user and the distributed endpoint devices. This intermediary system handles data chunking, encryption, device selection based on attributes, and coordinate management, thereby abstracting the complexity from the overall system while enabling scalable storage.
3Quantity of substance
If endpoint devices with limited processing power are used for storage, then hardware resource requirements are reduced, but data retrieval speed and performance deteriorate
Solution Approach 1:
The system dynamically adjusts the number of data chunks and their distribution based on the processing capabilities, bandwidth, and uptime of each endpoint device. Devices with higher capabilities can handle more chunks or larger data portions, optimizing retrieval speed while still utilizing devices with limited resources for storage capacity.
4Reliability
If data redundancy is increased to ensure availability, then data accessibility is improved, but storage efficiency deteriorates due to duplicated data portions
Solution Approach 1:
The patent segments data into encrypted chunks and distributes them across multiple devices. Redundancy is achieved by replicating specific chunks across selected devices based on availability requirements, rather than duplicating entire files. This segmented approach improves data availability while maintaining storage efficiency by only replicating necessary portions.
Data Source
AI summary
A system is configured to allocate storage space on existing devices within the entity's networked system to create cloud storage space. In particular, unallocated space on computing devices, typically user devices, within an entity's network is utilized as a cloud data repository. Cloud data is indexed, divided into chunks, encrypted, and stored on numerous disparate endpoint devices connected to the network. Copies of cloud chunk data may be duplicated across multiple endpoint devices to allow for data redundancy, thereby ensuring cloud data uptime according to the availability needs of the entity. Cloud data may further be allocated to different devices based on regional data restrictions. In this way, the system provides an efficient and secure way to generate an internal cloud data storage repository within an entity's networked system.