Virtual Appliance Manager for Dynamic Resource Throttling
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Solution Overview
Problem
Existing information handling systems, particularly consumer electronics platforms, lack flexibility in resource allocation and management, leading to issues such as over-subscription of resources, limited personalization, and inability to dynamically allocate CPU and peripheral resources like GPUs and network controllers, which can result in conflicts and compromised performance.
Innovation Solution
A system that includes a virtual appliance manager to configure and throttle resources based on priority, ensuring no over-subscription by automatically adjusting resource allocation, using heuristic prioritization, and providing user notifications and resolution options, while maintaining control across resources like CPU, GPU, and I/O devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resources are allocated statically to virtual machines, then resource allocation is simple and predictable, but resource utilization efficiency deteriorates and flexibility is reduced
Solution Approach 1:
The patent implements dynamic resource allocation by allowing virtual machines to request additional resources when needed and to release resources when no longer needed. The resource manager dynamically adjusts resource allocation based on current system conditions and VM requirements, transforming the static allocation model into a dynamic one that improves utilization efficiency while maintaining manageable complexity through automated decision-making processes.
Solution Approach 2:
The system changes the allocation parameters of computational resources (CPU, memory, I/O) dynamically based on demand. Instead of fixed parameter assignments, the resource manager adjusts parameters such as CPU time slices, memory allocation sizes, and I/O bandwidth limits in response to VM requests and system conditions, enabling flexible resource utilization without requiring complex manual configuration.
2Adaptability or versatility
If more virtual machines are deployed to increase service capacity, then system versatility improves, but resource over-subscription conflicts increase
Solution Approach 1:
The patent implements a feedback mechanism where virtual machines communicate their resource needs and current resource availability is monitored. The resource manager receives feedback from VMs about their performance and resource requirements, and adjusts allocations accordingly. This feedback loop prevents over-subscription conflicts by ensuring that resource allocation decisions are based on actual system conditions and VM needs, maintaining reliability while supporting increased service capacity.
Solution Approach 2:
Virtual machines are empowered to self-manage their resource allocations by requesting additional resources when needed and releasing resources when no longer required. This self-service approach allows the system to support more VMs without increasing management complexity, as each VM autonomously participates in resource allocation decisions, reducing conflicts through decentralized control while maintaining overall system reliability.
3Reliability
If fixed CPU cores are dedicated to particular applications, then application performance is guaranteed, but resource flexibility and dynamic allocation capability deteriorate
Solution Approach 1:
The patent segments CPU resources into time slices rather than dedicating entire cores to specific applications. Instead of allocating fixed physical cores, the system divides CPU time into manageable segments that can be dynamically assigned to different VMs based on their current needs. This segmentation approach maintains performance guarantees by ensuring each VM receives adequate CPU time while preserving flexibility to reallocate segments dynamically without being constrained by fixed core assignments.
4Reliability
If resource throttling is implemented to prevent over-subscription, then resource allocation reliability improves, but system complexity and management overhead increase
Solution Approach 1:
The patent reduces management overhead by implementing self-service mechanisms where virtual machines autonomously request and manage their own resource allocations. Instead of requiring centralized manual throttling control, VMs communicate their needs directly to the resource manager, which automatically adjusts allocations. This self-service approach maintains reliable resource allocation by preventing over-subscription through automated decision-making while significantly reducing the complexity and overhead of manual resource management.
Data Source
AI summary
A system for enabling throttling of resources, including central processing units (CPUs) and peripherals, on a virtualization-enabled information handling system such as a CE type information handling system is set forth. With the system for enabling throttling of resources, each virtual appliance within an information handling system is configured with its resource needs.