Virtual Machine Resource Negotiation via Dynamic Agents
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Solution Overview
Problem
In network computing environments, it is challenging to optimally allocate resources due to dynamic workloads and scarcity, making it difficult to predict when resource needs will spike and for how long, leading to inefficiencies in resource utilization.
Innovation Solution
Implementing resource agents within virtual machines that monitor and negotiate resource allocation patterns, updating usage data in a resource availability map, and facilitating sharing of resources between virtual machines to meet operational requirements or surplus thresholds, thereby optimizing resource distribution.
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 when workloads are dynamic
Solution Approach 1:
The patent implements dynamic resource allocation by enabling virtual machines to negotiate resource sharing in real-time based on current workload conditions. The system transitions from static pre-allocation to dynamic negotiation, where resource agents continuously monitor usage patterns and adjust sharing arrangements according to actual demand, thereby improving resource utilization efficiency while adapting to changing workload conditions
Solution Approach 2:
The patent employs feedback mechanisms through resource agents that monitor resource usage patterns and provide information about current and projected resource needs. This feedback loop enables the system to adjust resource allocation dynamically, with virtual machines communicating their resource requirements and availability to optimize overall resource utilization while maintaining operational requirements
2Productivity
If resources are shared dynamically among virtual machines, then resource utilization efficiency improves, but the complexity of monitoring and negotiating resource allocation increases
Solution Approach 1:
The patent implements self-service mechanisms where virtual machines autonomously negotiate resource sharing through their own resource agents. Each virtual machine's resource agent independently monitors its own resource usage, identifies surplus or shortfall conditions, and initiates negotiations with other virtual machines without requiring centralized coordination, thereby simplifying operation while achieving dynamic optimization
Solution Approach 2:
The patent introduces resource agents as intermediary components that facilitate resource negotiation between virtual machines. These agents act as mediators that monitor resource usage, communicate needs and availability, and coordinate sharing arrangements, thereby managing the complexity of dynamic resource sharing while maintaining ease of operation for the underlying virtual machines
3Reliability
If virtual machines have guaranteed minimum resources, then operational reliability is ensured, but resource flexibility deteriorates when other virtual machines need resources
Solution Approach 1:
The patent applies partial action by allowing virtual machines to guarantee minimum operational resources while permitting temporary borrowing of additional resources when needed. The resource sharing arrangement enables virtual machines to maintain their operational requirements through guaranteed minimum allocations while providing flexibility to acquire additional resources through negotiation, thereby achieving both reliability and adaptability
Solution Approach 2:
The patent implements dynamic resource allocation that adjusts the balance between guaranteed minimum resources and flexible shared resources based on real-time conditions. When workload conditions change, the system dynamically renegotiates resource sharing arrangements, allowing virtual machines to temporarily access additional resources while maintaining their operational reliability through the negotiation mechanism
Data Source
AI summary
Virtual machines within a network computing environment negotiate among themselves with regard to the sharing of resources via respective resource managers. The resource agent monitors resource allocation patterns of its virtual machine and responsively updates usage data in a resource availability map and compares the updated usage data to a minimum operational requirements threshold and a surplus amount threshold. If the updated usage fails to meet the minimum operational requirements threshold, the resource agent determines a needed shortfall amount of resources, searches the resource availability map for offers of the shortfall from resource agents, and sends out a request to a resource agent offering the shortfall amount. If the updated usage data meets the minimum operational requirements threshold, the resource agent determines a surplus amount of a resource that exceeds the surplus amount threshold and creates and broadcasts an offer of the surplus amount to the other resource agents.