Distributed Lock Mechanism for Scalable Data Acquisition Systems
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Solution Overview
Problem
Large-scale data acquisition systems face challenges in managing concurrent data processing across multiple sensors, as centralized storage mechanisms struggle to keep up with the high volume and speed of data influx, leading to inefficiencies and increased costs.
Innovation Solution
Implementing a distributed lock mechanism across storage nodes, where each event is assigned a unique identifier and hashed to determine the responsible node for locking, allowing for scalable and efficient data processing without a single point of failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a centralized storage mechanism is used to manage data from multiple sensors, then data consistency can be maintained, but the system cannot keep up with high data volume and speed, leading to inefficiencies and increased costs
Solution Approach 1:
The patent divides the centralized storage mechanism into multiple distributed storage nodes, each capable of independently storing and managing data events. This segmentation allows the system to process higher data volumes in parallel, improving productivity while distributing the complexity across multiple simpler nodes rather than one complex centralized system.
Solution Approach 2:
The patent introduces a distributed architecture dimension to the storage system, transitioning from a single centralized point to a multi-node distributed network. This dimensional change enables the system to scale horizontally, handling increased data throughput without proportionally increasing the complexity of individual storage components.
2Adaptability or versatility
If a distributed storage model is implemented to handle large data volumes, then system scalability is improved, but managing concurrent data processing across multiple nodes becomes challenging
Solution Approach 1:
The patent implements a locking mechanism that performs preliminary actions before data processing begins. Each storage node acquires locks on specific data events before processing, which pre-establishes a consistent state and avoids conflicts during concurrent operations. This preliminary locking simplifies the management of concurrent processing across distributed nodes.
Solution Approach 2:
The patent introduces a locking mechanism as an intermediary between multiple storage nodes and the data events they process. This intermediary coordinates access to shared resources, enabling scalable distributed storage while managing concurrent processing challenges through structured lock acquisition and release protocols.
3Reliability
If a centralized lock mechanism is used to prevent simultaneous processing of the same event, then data consistency is maintained, but the system creates a single point of failure and reduces processing efficiency
Solution Approach 1:
The patent segments the centralized lock mechanism into distributed locks held by individual storage nodes. Each node manages its own locks independently, eliminating the single point of failure in centralized locking. This segmentation maintains data consistency through localized lock management while enabling efficient concurrent processing across multiple nodes.
Solution Approach 2:
The patent implements dynamic lock management where locks are acquired and released based on real-time processing needs. Storage nodes dynamically acquire locks on specific events when needed and release them when processing is complete, allowing flexible concurrent access patterns that maintain consistency while maximizing processing efficiency.
4Productivity
If more storage nodes are added to increase processing capacity, then system scalability is improved, but the storage burden on each node increases
Solution Approach 1:
The patent segments the storage burden across multiple nodes, with each node responsible for specific data events. This segmentation allows the system to increase processing capacity by adding nodes without proportionally increasing the storage burden on each individual node, as the load is distributed rather than accumulated.
Solution Approach 2:
The patent implements local quality by assigning specific data events to specific storage nodes based on distributed locking principles. Each node optimizes its storage for its assigned events, reducing redundant storage across the system and allowing capacity expansion without linearly increasing total storage requirements.
Data Source
AI summary
Systems and methods for managing locks in a data acquisition system with a distributed data storage are disclosed. In embodiments, a storage node of a data acquisition system with a plurality of storage nodes receives a request for an unprocessed event, where portions of the event data are stored across the plurality of storage nodes. One node of the plurality of nodes holds the lock value for the event. The node receiving the request searches for an event where it stores the lock value that is unlocked. If none is found, the node receiving the request forwards the request to a second node, which repeats the search.