Adaptive Memory Allocation for Autonomous Driving Data Storage
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Solution Overview
Problem
Autonomous driving analysis data storage devices face memory space limitations, leading to potential shortages due to the capacity constraints of existing storage solutions, which can hinder the ability to store data required for liability determination in accidents over extended periods.
Innovation Solution
A storage device with adaptive memory management, utilizing a controller to monitor target information, predict memory region shortages, and dynamically adjust policies or allocate additional memory regions to store autonomous driving analysis data, ensuring sufficient storage capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If storage devices provide fixed memory space for autonomous driving analysis data, then device complexity is reduced, but memory space becomes insufficient when large volumes of data need to be stored
Solution Approach 1:
The patent implements dynamic memory region allocation where the first memory region size is not fixed but can be adjusted based on prediction results. The controller dynamically changes the memory region size to match predicted data generation patterns, allowing the system to adapt to varying storage requirements without permanently increasing complexity.
Solution Approach 2:
The system performs preliminary prediction of data generation patterns and memory shortage conditions before actual storage needs arise. By predicting future memory requirements in advance, the controller can proactively adjust memory region sizes and perform data migration or deletion operations before storage capacity is exhausted, preventing data loss while maintaining manageable complexity.
2Quantity of substance
If storage devices increase memory capacity to store more autonomous driving analysis data, then storage capacity is improved, but device cost and complexity increase
Solution Approach 1:
Instead of statically increasing memory capacity, the system dynamically adjusts the usable portion of the memory device through configurable memory regions. The first memory region for autonomous driving data and the second memory region for other data can be resized based on actual needs, allowing flexible storage capacity optimization without permanently increasing device complexity.
Solution Approach 2:
The memory device serves multiple functions through divided memory regions: the first memory region stores autonomous driving analysis data while the second memory region stores other data. This multi-functional approach allows a single memory device to handle diverse storage requirements, reducing the need for separate dedicated storage components and thereby controlling overall device complexity.
3Reliability
If storage devices use simple fixed memory allocation, then ease of operation is improved, but inability to predict and prevent memory shortage reduces reliability
Solution Approach 1:
The system implements a feedback loop where the controller continuously monitors data generation patterns, predicts future memory requirements, and adjusts memory region allocation accordingly. This closed-loop control ensures that memory shortage conditions are predicted and prevented, significantly improving data storage reliability while keeping the complexity manageable through automated prediction algorithms.
Solution Approach 2:
The prediction function performs preliminary assessment of memory shortage conditions before they actually occur. By analyzing historical data generation patterns and predicting future trends, the system can proactively adjust memory allocation, migrate data, or delete unnecessary data in advance, ensuring continuous reliable storage without requiring complex real-time intervention mechanisms.
4Reliability
If storage devices dynamically adjust memory regions to prevent shortage, then data storage reliability is improved, but device complexity increases
Solution Approach 1:
The system employs dynamic memory region adjustment where the size of the first memory region is modified based on prediction outcomes. This dynamic adaptation allows the system to maintain sufficient memory space for autonomous driving data under varying conditions while using automated algorithms to manage the complexity of region resizing, data migration, and deletion operations.
Data Source
AI summary
A storage device includes a memory device including a first memory region configured to store autonomous driving analysis data and a controller configured to control a memory operation of the memory device, wherein the controller includes a management circuit configured to monitor a plurality of pieces of target information related to autonomous driving, predict a shortage of the first memory region, and perform an operation to increase a free space of the first memory region based on a result of the prediction.