File Transfer Server Memory Management via Dynamic Speed Throttling
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Solution Overview
Problem
Current solutions for managing congestion in network components, such as servers, often result in service denial or system crashes due to memory overload, and existing methods like clustering or adaptive transfer have limitations, including security vulnerabilities and inefficiencies in resource distribution.
Innovation Solution
Implementing a system with a load balancer and speed limiter modules that use artificial intelligence to predict congestion scenarios by analyzing client behavior and network status, throttling requests to prevent memory overload without denying service, and dynamically controlling request speeds to ensure completion of critical transfers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If denial of service is implemented based on memory threshold, then memory overload is prevented, but service continuity is disrupted
Solution Approach 1:
The patent implements dynamic speed adjustment for file transfers based on real-time memory usage monitoring. Instead of static denial of service, the system continuously adapts transfer speeds to maintain memory usage within safe thresholds while keeping services operational. This resolves the contradiction by making the protection mechanism dynamic rather than binary.
Solution Approach 2:
The system employs feedback mechanisms where memory usage is continuously monitored and used to adjust transfer speeds. The monitoring component tracks memory consumption and feeds this information back to the speed control component, which adjusts transfer parameters accordingly. This closed-loop feedback system prevents memory overload while maintaining service continuity through adaptive control.
2Productivity
If multiple requests are processed concurrently, then service efficiency is improved, but memory consumption increases leading to system crashes
Solution Approach 1:
The patent applies partial action by allowing multiple requests to be processed concurrently but limiting the total resource consumption to a safe threshold. Instead of processing all requests at full speed (excessive action), the system throttles transfer speeds to ensure memory usage remains within safe limits while still maintaining parallel processing benefits.
Solution Approach 2:
The system dynamically changes transfer parameters (speed, buffer size, chunk size) based on current system state. When memory usage approaches thresholds, the system adjusts these parameters to reduce memory pressure while maintaining request processing. This allows concurrent processing to continue safely by adapting parameters in real-time.
3Productivity
If file transfer speed is increased, then productivity is improved, but memory overload risk increases
Solution Approach 1:
The patent implements dynamic speed control where transfer speed is not fixed but continuously adjusted based on memory usage conditions. The system can operate at high speeds when memory is available and automatically throttles when thresholds are approached, making the speed parameter dynamic rather than static.
Solution Approach 2:
The system performs preliminary monitoring of memory conditions before and during file transfers. By proactively detecting when memory usage approaches unsafe levels, the system can preemptively adjust transfer speeds to prevent overload, rather than reacting after the problem occurs.
4Productivity
If clustering is implemented to distribute load, then system capacity is improved, but complexity and cost increase
Solution Approach 1:
The patent implements self-service through automated monitoring and control mechanisms that manage memory usage without external intervention. The system autonomously detects memory conditions and adjusts transfer parameters, eliminating the need for complex manual load balancing or clustering architectures.
Data Source
AI summary
Certain example embodiments relate to techniques for addressing resource utilization issues in network components (e.g., file transfer servers running out of memory, for example) by identifying and predicting scenarios that are likely to cause problems, and handling them gracefully, without having to deny service completely. Based on current runtime status information and a prediction of how a given request will impact the server and/or the network, a determination is made regarding whether that request is to be accepted by the server. If the total resource usage of the server exceeds or is likely to exceed a threshold: the speed at which requests being processed are being handled is controlled, such that (a) speeds of all but some of the requests are throttled, (b) throttled requests are neither terminated nor allowed to timeout, (c) as non-throttled requests are completed, requests that are throttled have their speeds increased in a predetermined manner.