Hibernation Control for Nonvolatile Memory Lifespan
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Solution Overview
Problem
Electronic devices face challenges in reducing power consumption while minimizing latency and prolonging the life of nonvolatile memory when entering hibernation states, as frequent hibernations lead to increased wear and tear on storage media, and users experience lag due to sequential data loading from nonvolatile memory.
Innovation Solution
Implementing a method to determine and preload snapshot data likely to be requested by users upon resuming from hibernation, limiting the frequency of hibernation entries by setting cumulative and session thresholds to extend the life of nonvolatile memory, and optimizing data transfer rates to reduce perceived latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the device enters hibernation state frequently to reduce power consumption, then power consumption is reduced and battery life is prolonged, but the life of nonvolatile memory is reduced due to increased wear and tear
Solution Approach 1:
The system performs preliminary actions by determining which snapshot data is likely to be requested by users before actually resuming from hibernation. It preloads this identified data during the hibernation state, so that when the user does request it, the data is already available in volatile memory. This preliminary preparation reduces the need for frequent hibernation entries while still maintaining power savings and memory lifespan.
2Use of energy by moving object
If the device enters hibernation state to reduce power consumption, then power consumption is reduced, but users experience lag due to sequential data loading from nonvolatile memory
Solution Approach 1:
The system performs preliminary actions by determining which snapshot data is likely to be requested by users before actually resuming from hibernation. It preloads this identified data during the hibernation state, so that when the user does request it, the data is already available in volatile memory. This preliminary preparation reduces the need for frequent hibernation entries while still maintaining power savings and memory lifespan.
Solution Approach 2:
The system dynamically adjusts the hibernation strategy by implementing cumulative and session thresholds. Instead of a static hibernation policy, the system adapts its behavior based on usage patterns, allowing it to optimize between power consumption and user-perceived latency in real-time based on actual device usage conditions.
Data Source
AI summary
Devices, systems and methods are disclosed for limiting a number of hibernations based on a finite lifetime expectancy of nonvolatile memory. As the nonvolatile memory has a finite lifetime expectancy, a device may determine cumulative thresholds and associated session thresholds and may limit a frequency that the device hibernates. For example, the device may determine a cumulative number of hibernations and associate the cumulative number of hibernations with a cumulative threshold. The device may determine a session threshold corresponding to the cumulative threshold and may limit a number of hibernations using the session threshold. For example, the device may enter a hibernation state up to the session threshold and thereafter may enter a suspended state instead.


