Access Machine Load Processing with Delayed Cognitive Load
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Solution Overview
Problem
Existing load processing methods fail to accurately determine the load received by access machines in network applications, leading to potential overload conditions, especially in interactive live broadcast services where sudden changes in user interactions can cause bottlenecks.
Innovation Solution
A method and device that calculate the actual load by considering both the reported load amount and a delayed cognitive load amount, determining a first time difference between the scheduling request and access, and summing these to identify if the access machine is operating at or near its maximum threshold, thereby preventing overload by allocating user terminals effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only the reported load amount is used to determine current load, then the measurement is simple, but the load determination is inaccurate due to delayed cognitive load
Solution Approach 1:
The system performs preliminary calculation of the delayed cognitive load amount before making load determination decisions. By pre-calculating the load that will be allocated in the current period based on historical allocation data and time differences, the system ensures accurate load assessment before overload conditions occur, rather than reacting after the fact.
Solution Approach 2:
The patent introduces an intermediary calculation component that bridges the gap between reported load amounts and actual system load. This intermediary calculates the delayed cognitive load amount as a mediating value that, when added to the reported load, provides a comprehensive view of the actual load, resolving the inaccuracy without requiring complete system restructuring.
2Reliability
If the load threshold is set low to prevent overload, then system reliability improves, but resource utilization decreases
Solution Approach 1:
By pre-calculating the delayed cognitive load and adding it to the reported load before comparison with the threshold, the system identifies approaching overload conditions early. This allows the threshold to be set at optimal levels without frequent overloads, as the predictive nature of the calculation prevents sudden capacity exhaustion that would force conservative threshold settings.
Solution Approach 2:
The system implements feedback by continuously monitoring the relationship between reported load, delayed cognitive load, and actual system performance. This feedback loop allows dynamic adjustment of resource allocation decisions, maintaining high resource utilization while preventing overload through informed threshold management based on accurate load predictions.
Data Source
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AI summary
The present disclosure relates to a service load processing method and device. The method comprises: a current time and a load amount reported at the current time by an access machine is obtained , a delayed cognitive load amount allocated to the access machine is obtained from a period between a first time point obtained by subtracting a first time difference from the current time and the current time, the first time difference including a time difference between initiation of the scheduling request by a user terminal and access to the access machine by the user terminal, taking a sum of the load amount reported at the current time and the delayed cognitive load amount is taken as the actual load amount reported by the access machine at the current time, whether the access machine is running under an overload condition is determined by comparing the actual load amount reported by the access machine at the current time with a maximum load amount threshold for the access machine. For the service load processing method and device, since the load amount corresponding to the user terminal that has been allocated to the access machine and delayed for access to the access machine is considered, the overloading of the access machine is prevented and load amount that has been received by the access machine can be accurately determined.