Dynamic Resource Allocation in Grid Computing
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Solution Overview
Problem
In data centers, server clusters often inefficiently manage unpredictable workloads, leading to underutilization of resources due to over-provisioning for peak demands, which results in idle servers and suboptimal resource allocation in grid computing environments.
Innovation Solution
A method for dynamically allocating and deallocating computational resources in a grid computing environment, allowing for the installation, execution, and removal of applications on computer devices while recording modifications to revert the system to its original state, enabling efficient resource utilization and management through a hierarchical grid manager system using Open Grid Services Infrastructure (OGSI) and Web Service Definition Language (WSDL) interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If servers are over-provisioned to handle peak workload demands, then reliability and connectivity are improved, but resource utilization deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation where the grid computing system continuously monitors workload demands and automatically adjusts resource allocation in real-time. The system transitions from static over-provisioning to dynamic provisioning, allowing resources to be allocated and deallocated based on actual demand patterns, thereby maintaining reliability while optimizing utilization.
Solution Approach 2:
The system changes the parameter of resource allocation from fixed to variable based on workload characteristics. By monitoring and analyzing workload patterns, the system adjusts allocation parameters dynamically, allocating additional resources only when peak demands occur and releasing them when demand subsides, resolving the contradiction between reliability and resource utilization.
2Stability of the object's composition
If static resource allocation is used to ensure availability, then system stability is improved, but adaptability to workload changes deteriorates
Solution Approach 1:
The system performs preliminary actions by establishing baseline resource allocation and monitoring mechanisms in advance. When workload changes are detected, the system has pre-configured protocols and procedures that enable rapid adaptation without compromising stability. This preliminary preparation allows the system to respond efficiently to workload variations while maintaining overall system stability.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors workload characteristics and allocation effectiveness. This feedback loop enables the system to learn from past performance and adjust future allocations accordingly, achieving both stability through consistent monitoring and adaptability through data-driven adjustments.
3Reliability
If resources are allocated to handle peak demands, then service quality is improved, but cost efficiency deteriorates
Solution Approach 1:
The system employs periodic action by allocating resources in cycles corresponding to workload patterns. Instead of continuous over-provisioning, the system periodically adjusts resource allocation based on detected workload trends, activating additional resources only during peak periods and deactivating them during normal operation, thereby maintaining service quality while improving cost efficiency.
Solution Approach 2:
The patent implements discarding and recovering of allocated resources. When peak demands subside, the system safely deallocates (discards) excess resources that are no longer needed, and recovers them for future use or returns them to the resource pool. This mechanism eliminates wasted resources while ensuring service quality is maintained during actual demand periods.
Data Source
AI summary
A method includes requesting a computer in a network to install a first application and execute the first application, transferring one or more files to the computer, making modifications to the computer to install and execute the first application on the computer while recording the modifications, the modifications comprising allocating a resource to the first application, halting the first application on the computer, and reversing a portion of the modifications to the computer according to the recorded modifications. The reversing includes deallocating the resource from the first application. The method also includes making modifications to the computer to install and execute a second application on the available computer while recording the modifications, where the modifications include allocating the resource to the second application.