Adaptive Compression in Idempotent Message Stores Under Memory Constraints
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Solution Overview
Problem
Existing messaging architectures face issues such as duplicate message handling, resource inefficiency, and increased compute load due to duplicate messages, particularly in resource-constrained edge devices, leading to inaccurate data and excessive power consumption.
Innovation Solution
Implementing an idempotent data store that filters out duplicate messages using message identifiers and employs adaptive compression techniques to manage storage across a cluster of nodes, optimizing memory usage and reducing compute load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If duplicate messages are processed in existing messaging architectures, then message delivery completeness is improved, but processor cycles and power consumption increase
Solution Approach 1:
The patent extracts the duplicate detection function from the main message processing flow by implementing an idempotent data store that stores message identifiers separately. This allows the system to filter out duplicate messages before full processing occurs, reducing unnecessary power consumption while maintaining complete message delivery.
Solution Approach 2:
The system performs preliminary action by checking message identifiers against the idempotent data store before processing message payloads. This preliminary filter prevents duplicate messages from consuming processor cycles and power during full processing, while ensuring no valid messages are lost.
2Reliability
If duplicate messages are processed in existing messaging architectures, then message delivery completeness is improved, but compute load increases
Solution Approach 1:
The patent extracts the duplicate detection function from the main message processing flow by implementing an idempotent data store that stores message identifiers separately. This allows the system to filter out duplicate messages before full processing occurs, reducing unnecessary compute load while maintaining complete message delivery.
Solution Approach 2:
The system performs preliminary action by checking message identifiers against the idempotent data store before processing message payloads. This preliminary filter prevents duplicate messages from consuming processor cycles during full processing, while ensuring no valid messages are lost.
3Quantity of substance
If compression is applied to message identifiers in the data store, then memory usage is reduced, but access time increases
Solution Approach 1:
The patent implements dynamic compression where the compression level and algorithm are adjusted based on current system conditions such as memory availability and access frequency. When memory is constrained, compression is applied; when access speed is critical, compression is reduced or bypassed, optimizing the trade-off dynamically.
Solution Approach 2:
The system changes parameters such as compression ratio and data structure organization based on workload characteristics. For frequently accessed message identifiers, less aggressive compression is used to maintain fast access. For less frequently accessed identifiers, higher compression ratios reduce memory usage without significantly impacting overall system performance.
Data Source
AI summary
Systems and methods for adaptive compression for idempotent data stores in computer messaging are generally described. In some examples, a first node may receive a first message that includes a first message identifier and first payload data. In some examples, the first node may determine that a respective available amount of storage of each node of a plurality of nodes is below a first threshold available amount of storage. In some cases, the plurality of nodes may include the first node. The first node may receive a compression key from a primary node of a cluster including the plurality of nodes. The first node may compress a second message identifier stored in a data structure of the first node using the compression key.