Predictive Resource Allocation for Network Usage Peaks
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Solution Overview
Problem
Resource management in dispersed networks faces challenges in efficiently allocating resources based on constraints and metrics, particularly in predicting and managing elevated usage instances across a dispersed Internet protocol capable network.
Innovation Solution
A system that determines resource utilization profiles, continuously monitors resource usage, predicts elevated usage instances, and reallocates resources by analyzing patterns and user behavior to optimize resource availability and usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If resources are allocated based on predefined constraints and protocols, then resource allocation follows established rules, but the system cannot adapt to unpredictable elevated usage instances
Solution Approach 1:
The system performs preliminary actions by continuously monitoring resource utilization profiles and predicting future elevated usage instances before they occur. This allows the system to proactively allocate additional resources in advance, rather than reactively responding to constraints and protocols after elevated usage is detected.
2Measurement precision
If the system continuously monitors resource utilization to predict elevated usage instances, then resource allocation accuracy improves, but computational resources and processing time increase
Solution Approach 1:
The monitoring system serves multiple functions simultaneously: it tracks current resource utilization, identifies patterns in usage behavior, predicts future elevated instances, and provides data for optimization decisions. This multi-functionality reduces the need for separate systems and minimizes overall computational energy consumption while maintaining high prediction accuracy.
3Reliability
If additional resources are pre-allocated for predicted elevated usage instances, then resource availability during peak periods improves, but resource utilization efficiency during normal periods decreases
Solution Approach 1:
The system dynamically adjusts resource allocation based on real-time monitoring and predictive analysis. Instead of static pre-allocation, resources are flexibly allocated only when and where needed for predicted elevated usage instances, while being released for other uses during normal periods. This dynamic approach maintains high reliability during peaks while preserving overall utilization efficiency.
Data Source
AI summary
Systems, computer program products, and methods are described herein for predictive usage of resources across a dispersed Internet protocol capable network connecting devices electrically attached to the network. The present invention is configured to determine resource utilization profile associated with a user; continuously monitor the resource utilization profile of the user to track the use of the one or more resources allocated to the user over a predetermine period of time; determine one or more elevated usage instances; predict, via the resource prediction application, that at least one of the one or more elevated usage instances is scheduled to occur; determine one or more resources across the dispersed network for the user for processing during the at least one of the one or more elevated usage instances; and reallocate the one or more determined resources to the user.