Application Prioritization Manager for Adaptive Network Resource Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing prioritization mechanisms in network data transfer are limited by their applicability and effectiveness, failing to adapt to diverse user needs, application types, and network conditions, leading to inefficiencies and user dissatisfaction.
Innovation Solution
An application prioritization manager (APM) uses machine learning models to dynamically allocate network resources based on user preferences, application types, and network conditions, assigning scores to applications for prioritization or deprioritization, leveraging factors like user interaction, application state, and network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional prioritization mechanisms are used to regulate data packet flow, then network congestion is avoided and latency is reduced, but the system lacks adaptability to diverse user needs, application types, and network conditions
Solution Approach 1:
The patent implements dynamic prioritization by continuously monitoring application behavior, user interactions, and network conditions to adjust priority levels in real-time. The system transitions from static priority assignments to dynamic adjustments based on current system state, enabling adaptability while managing complexity through event-driven updates rather than continuous reconfiguration.
Solution Approach 2:
The system changes priority parameters dynamically based on multiple factors including application type, user behavior patterns, network conditions, and resource availability. By modifying priority levels as adjustable parameters rather than fixed values, the system achieves versatility across different scenarios while maintaining a manageable underlying structure.
2Reliability
If network resources are allocated equally to all applications, then system simplicity is maintained, but network performance and user satisfaction deteriorate due to inability to prioritize critical applications
Solution Approach 1:
The patent implements self-service mechanisms where applications automatically register their requirements and the system autonomously monitors and adjusts priority levels based on observed behavior patterns. This reduces the need for manual configuration and complex centralized control, achieving reliable performance through distributed intelligence rather than complex centralized management.
Solution Approach 2:
The system employs feedback loops that continuously monitor network conditions, application performance, and user interactions to dynamically adjust resource allocation. This feedback mechanism enables the system to automatically optimize performance for critical applications while maintaining simplicity through rule-based responses to observed conditions rather than complex predictive models.
3Productivity
If prioritization mechanisms are explicitly enabled by applications, then implementation simplicity is maintained, but effectiveness deteriorates due to inability to handle background tasks and unattended applications
Solution Approach 1:
The patent implements self-service where applications automatically declare their priorities and the system autonomously manages resource allocation based on observed behavior. Background tasks and unattended applications are automatically detected and managed without requiring explicit user configuration, achieving high productivity while maintaining ease of operation through automatic detection and classification of application types.
Solution Approach 2:
The system performs preliminary classification of applications during installation or first launch, categorizing them by type and typical behavior patterns. This preliminary action enables the system to apply appropriate prioritization rules automatically from the start, improving resource utilization efficiency without requiring users to manually configure prioritization settings for each application.
Data Source
AI summary
The present application provides systems and methods for adaptive network resource allocation using application prioritization and deprioritization. An application prioritization manager (APM) receives data about an application, or other contextual data, from various components, and prioritizes the application's network resources among other applications that are also prioritized. The APM generates scores for different factors that are derived from the data, such as application type, application network usage, whether an application is minimized, or whether an application is in focus, among others. The APM combines the scores for the different factors into a combined score for the application, and prioritizes the application among other applications based on their combined scores. The APM selects a prioritization mechanism for the application based on the combined score, such as traffic shaping, traffic policing, traffic scheduling, or other techniques that control aspects of the network traffic.