Energy Storage Message Rate Balancing to Prevent Proxy Queue OOM
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Solution Overview
Problem
Energy storage devices and clouds experience unstable production and consumption rates, leading to memory overload in proxy servers and inefficient system operation due to Out Of Memory (OOM) exceptions, which are currently addressed only through post-event repairs that waste resources and affect efficiency.
Innovation Solution
Implement a method using a proxy server with a service memory queue and exception notification queue to monitor and adjust production and consumption rates adaptively, calculating variation coefficients and accumulation rates to prevent OOM exceptions by adjusting message pushing based on real-time data and thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the energy storage device pushes production messages at high rate when reconnected, then message delivery completeness is improved, but the proxy server memory load increases causing OOM exceptions
Solution Approach 1:
The patent applies dynamics by making the message pushing rate adjustable and adaptive. The energy storage device dynamically adjusts its message pushing rate based on the consumption rate feedback from the cloud and the accumulation rate in the proxy server queue. When the queue accumulation rate exceeds a threshold, the device automatically reduces its pushing rate to prevent memory overload, while still ensuring eventual delivery of all messages.
Solution Approach 2:
The patent implements feedback mechanisms where the cloud consumes messages at a stable rate and provides feedback information to the energy storage device about the consumption rate. The proxy server also monitors queue accumulation rates and provides feedback. This feedback loop enables the energy storage device to adjust its production rate adaptively, balancing message delivery completeness with preventing proxy server memory overload.
2Stability of the object's composition
If the cloud consumes production messages at reduced rate due to component blocking or network fluctuation, then system stability is improved, but message accumulation increases leading to OOM exceptions
Solution Approach 1:
The patent applies dynamics by enabling the energy storage device to dynamically adjust its message pushing rate in response to changes in cloud consumption rate. When the cloud's consumption rate decreases due to component blocking or network fluctuation, the energy storage device detects this through feedback and automatically reduces its pushing rate accordingly, preventing excessive message accumulation in the proxy server while maintaining system stability.
Solution Approach 2:
The patent implements preliminary action by having the energy storage device proactively adjust its message pushing rate before the proxy server memory becomes overloaded. Through continuous monitoring of queue accumulation rates and consumption rates, the device predicts potential overload conditions and reduces pushing rate in advance, preventing OOM exceptions rather than reacting after they occur.
3Reliability
If post-event repair is used to fix OOM exceptions by restarting devices, then system reliability is restored, but operation efficiency decreases and resources are wasted
Solution Approach 1:
The patent implements preliminary action by preventing OOM exceptions before they occur through real-time monitoring and adaptive rate adjustment. The energy storage device continuously monitors queue accumulation rates and cloud consumption rates, and proactively adjusts its message pushing rate to keep the proxy server queue within safe memory limits. This eliminates the need for post-event repairs and system restarts, maintaining both reliability and continuous operation efficiency.
Solution Approach 2:
The patent applies self-service by enabling the energy storage device to automatically monitor, detect, and correct imbalances between production and consumption rates without external intervention. The device autonomously adjusts its pushing rate based on feedback from the proxy server and cloud, self-correcting potential OOM conditions before they require manual repair or system restart, thereby eliminating waste of operation and maintenance resources.
Data Source
AI summary
A method for balancing production and consumption of an energy storage device and an electronic device are provided. When a production and/or consumption variation coefficient is greater than a corresponding threshold, a target data amount A of the production messages consumed by a cloud is acquired, an accumulation rate D is calculated according to a preset length B of a service memory queue and a data amount C of the production messages currently in the service memory queue, and/or, a consumption time E is acquired according to C and A. When D is greater than a preset rate or E is greater than a preset time, an exception notification message is pushed to an exception notification queue, so that the energy storage device determines a pushing amount of the production messages when the exception notification queue is updated, and pushes the production messages according to the pushing amount.