Modular Data Storage Location Maps for Seamless Capacity Expansion
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Solution Overview
Problem
Modular data storage systems face challenges in efficiently managing data distribution across multiple containers, making it difficult to quickly locate or remove data, especially when the number of containers changes, which can lead to administrative burdens and interruptions in access.
Innovation Solution
The implementation of location maps that deterministically map data objects to specific containers, allowing for the creation of new maps when the set of containers changes, enabling seamless expansion or diminishment of storage capacity without data copying, and optimizing data removal by grouping objects based on conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is distributed across multiple storage containers, then storage capacity is increased, but data location and removal becomes difficult and time-consuming
Solution Approach 1:
The patent introduces location maps as intermediary data structures that store mapping information between data objects and their container locations. These maps act as mediators between the distributed data and the system needing to access it, enabling efficient location without scanning all containers. The location maps contain pre-computed hash mappings that directly point to container locations, resolving the time loss issue while maintaining distributed storage capacity.
2Speed
If a map is used to store mapping of hash values across containers, then data location becomes faster, but system complexity increases
Solution Approach 1:
The patent segments the location mapping system into multiple location maps, where each map corresponds to a specific set of containers. This segmentation allows the system to manage complexity by dividing the overall mapping task into smaller, manageable pieces. Each location map is relatively simple in structure, and they can be independently created and maintained, reducing the overall system complexity while still providing fast access through the combined mapping capability.
3Adaptability or versatility
If containers are added or removed from the data store, then storage flexibility is improved, but data distribution and access continuity is disrupted
Solution Approach 1:
The patent implements preliminary action by creating new location maps in advance that reflect the updated container configuration before actual data migration occurs. When containers are added or removed, the system pre-generates location maps corresponding to the new container set, then uses these maps to guide subsequent data operations. This preliminary preparation ensures that data access continuity is maintained during transitions, as the new maps are ready to redirect access immediately when needed.
4Adaptability or versatility
If data is copied among containers when the map changes, then data distribution is updated, but computational intensity and time increase
Solution Approach 1:
The patent uses copying strategically by creating new location maps that reference the same physical data containers rather than physically moving data. When the container set changes, the system copies the mapping information into new location map structures that reflect the updated configuration, while the actual data remains in place. This approach updates data distribution information with minimal computational overhead, avoiding the energy-intensive process of physically copying data between containers.
Data Source
AI summary
The management of a data storage system. The system may store data objects that are subject to change in container sets. The data storage system uses location maps to map the data objects to a corresponding container. When there has been, or will be, a change in the availability of containers, a new location map is created which maps the data objects to a new potentially overlapping set of containers. New data objects are added to the new set of containers, and a data object is found by searching all location maps. As an alternative or as an addition to this system, data objects may be stored in a manner that they may be efficiently removed when a condition is met. A container is created which stores all data objects to be removed when the condition occurs. When the condition occurs, the container is removed.