Asymmetric Key Compression for Duplicate Message ID Storage
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Solution Overview
Problem
Duplicate messages in computer messaging systems can cause resource consumption and inaccurate data processing, particularly in resource-constrained edge computing devices, leading to issues like increased CPU usage and battery drain.
Innovation Solution
Implementing adaptive asymmetric-key compression for idempotent data stores that filter out duplicate messages by using message identifiers and adaptive resource management to store and compress data, ensuring messages are only processed once.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If duplicate messages are processed in messaging systems, then message delivery completeness is improved, but resource consumption (CPU, memory, battery) increases
Solution Approach 1:
The system performs preliminary action by storing message identifiers in an idempotent data store before processing the full message content. When a duplicate message is detected through the identifier, the system skips processing entirely, preventing wasted CPU cycles and battery drain while ensuring messages are only processed once.
Solution Approach 2:
The invention extracts the message identifier from the full message content and uses it as a standalone key for duplicate detection. This separation allows the system to filter duplicates using only the lightweight identifier before committing resources to processing the complete message, reducing unnecessary resource consumption.
2Reliability
If message identifiers are stored in data stores, then duplicate message detection is improved, but memory usage increases
Solution Approach 1:
The system changes the parameter of storage by compressing message identifiers using asymmetric-key compression algorithms. This transformation reduces the storage footprint of identifiers in the idempotent data store, allowing duplicate detection functionality to be maintained with reduced memory consumption.
Solution Approach 2:
The invention uses cryptographic hashing to create compressed representations of message identifiers. These hash copies serve as surrogate keys that occupy less storage space while maintaining the ability to uniquely identify and detect duplicate messages through comparison operations.
3Quantity of substance
If compression and decompression operations are performed, then storage capacity is improved, but CPU cycles increase
Solution Approach 1:
The system applies partial compression by only compressing message identifiers rather than entire messages, and only compressing when storage thresholds are exceeded. This selective approach provides storage benefits while minimizing the CPU overhead of compression operations, as identifiers are much smaller than full message content.
Solution Approach 2:
The invention implements periodic monitoring of storage thresholds and triggers compression operations only when necessary. This event-driven approach avoids continuous CPU-intensive compression, performing it only when storage capacity requirements dictate, thereby balancing storage optimization with CPU cycle conservation.
Data Source
AI summary
A method includes: receiving, by a server node, a first notification indicating that a first message received by a first node of a cluster of nodes is not a redundant message and cannot be stored by a data store of the nodes, wherein the nodes are managed by the server node; determining to invoke a compression process used to compress message identifiers stored in the first node; receiving a first public key associated with the first node; generating a compression key; generating a first encrypted compression key by encrypting the compression key with the first public key; sending, to the first node, the first encrypted compression key; and receiving, from the first node, a second notification of storing, in a compressed form using a key decrypted from the first encrypted compression key, at least one message identifier in a data store of the first node.