Resource Access Management via Projected Overload Rescheduling
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Solution Overview
Problem
Computing systems often face demand for resources that exceeds available capacity, leading to potential failures and the need for enhanced management of resource access.
Innovation Solution
A computer system that detects projected overload conditions by analyzing resource demand and available resources, identifies relevant server resources, generates and sends rescheduling requests to reschedule resource demands until after the projected overload, and provides access to resources at the rescheduled time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resource demand exceeds available capacity, then system reliability deteriorates due to potential failures, but allowing all resource demands would increase system complexity and resource utilization pressure
Solution Approach 1:
The system performs preliminary actions by detecting projected overload conditions before they occur and proactively rescheduling resource demands in advance. The resource management system analyzes future resource demand patterns and identifies potential overload situations prior to execution, allowing preemptive rescheduling to prevent failures rather than responding to failures after they occur.
Solution Approach 2:
The system implements feedback mechanisms where resource demand information is continuously monitored and fed back into the resource management system. This feedback loop enables the system to detect projected overload conditions by analyzing current and historical resource demand patterns, allowing dynamic adjustment of resource allocation decisions based on real-time system state information.
2Reliability
If resource demands are rescheduled to prevent overload, then system reliability improves, but time loss increases due to rescheduling delays
Solution Approach 1:
The system performs preliminary rescheduling actions before actual overload conditions occur by analyzing projected resource demand patterns. This advance planning allows the system to reschedule resource demands proactively, distributing the time loss across the planning horizon rather than concentrating it at the moment of failure, thereby maintaining overall system reliability.
Solution Approach 2:
The system dynamically adjusts resource demand schedules based on real-time and projected system conditions. The rescheduling mechanism is flexible and adaptive, allowing the system to optimize time loss by dynamically reallocating resources based on current demand patterns, historical data, and predicted future conditions rather than following fixed schedules.
3Productivity
If the system monitors and manages resource demands continuously, then resource utilization optimizes, but device complexity increases due to continuous monitoring and analysis requirements
Solution Approach 1:
The system uses feedback mechanisms to continuously monitor resource demand patterns and system utilization states. By analyzing this feedback information, the system identifies projected overload conditions and optimizes resource allocation decisions. The feedback loop enables continuous improvement of resource utilization by learning from historical data and adapting to changing conditions.
Solution Approach 2:
The resource management system performs self-service by automatically detecting projected overload conditions and rescheduling resource demands without requiring external intervention. The system monitors its own state, analyzes resource demand patterns, and executes rescheduling actions autonomously, reducing the need for complex external monitoring and control systems.
Data Source
AI summary
Methods and computer systems for managing access to resources in a computing environment. Detecting a projected overload condition from a projected demand for a resource. Identifying a server associated with a resource demand scheduled to be fulfilled prior to the projected overload condition. Generating a rescheduling request to reschedule the resource demand until after the projected overload condition. Sending the rescheduling request to the identified server. Providing access to the resource at a rescheduled time.