Dynamic Service Load Distribution in Asymmetrical Server Clusters
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Solution Overview
Problem
Conventional server load distributing systems fail to perform dynamic load distribution effectively in asymmetrical resource environments and struggle to promptly detect failures in computers, leading to inefficient service execution and potential interruptions.
Innovation Solution
A computer system with service load monitors, node load monitors, and service optimal allocation means that measure and reallocate loads across computers based on dynamic service and node ticket values, optimizing service execution and failure handling in asymmetrical environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional server load distributing systems use round-robin or weighted round-robin scheduling methods, then service requests can be distributed across multiple computers, but the system cannot effectively adapt to asymmetrical resource environments where computers have different capacities and service requirements
Solution Approach 1:
The patent implements dynamic service ticket values that are automatically adjusted based on real-time service execution status, computer performance metrics, and load conditions. This dynamic adjustment mechanism allows the system to adapt to asymmetrical resource environments by allocating more services to high-performance computers and fewer to lower-performance ones, resolving the contradiction between adaptability and productivity
Solution Approach 2:
The system employs feedback mechanisms where service load monitors and node load monitors continuously report service execution status and computer performance to the service optimal allocation means. This feedback loop enables automatic adjustment of service ticket values and reallocation of services based on actual system conditions, allowing the system to adapt to asymmetrical environments while maintaining high service execution efficiency
2Reliability
If the system uses static service allocation without dynamic adjustment, then system complexity is reduced, but the system cannot promptly detect failures or optimize resource utilization in asymmetrical environments
Solution Approach 1:
The patent implements self-service mechanisms where computers automatically monitor their own service execution status and performance metrics through service load monitors and node load monitors. The system autonomously detects failures, adjusts service ticket values, and reallocates services without external intervention, enhancing reliability while keeping the added complexity minimal and self-managing
Solution Approach 2:
The system performs preliminary actions by pre-configuring service optimal allocation means that automatically activates upon detecting service execution status changes. The monitors continuously prepare failure detection and the allocation means stands ready to reallocate services, ensuring prompt failure detection and response without requiring complex manual intervention structures
3Productivity
If service ticket values are manually configured without dynamic adjustment, then ease of operation is improved, but resource utilization efficiency deteriorates in asymmetrical environments with varying service loads
Solution Approach 1:
The system implements self-service by automatically calculating and adjusting service ticket values based on real-time service execution status, computer performance metrics, and load conditions. The service optimal allocation means autonomously optimizes resource allocation without manual configuration, achieving high resource utilization efficiency in asymmetrical environments while eliminating complex manual service configuration requirements
Solution Approach 2:
The feedback mechanism continuously monitors service execution status and computer performance, automatically adjusting service ticket values to optimize resource utilization. This eliminates the need for manual configuration while maintaining ease of operation, as the system self-optimizes based on actual conditions in asymmetrical environments
4Reliability
If the system reallocates services only upon failure detection through timeout, then system complexity is minimized, but service interruption time increases and availability decreases
Solution Approach 1:
The system performs preliminary failure detection by continuously monitoring service execution status through service load monitors and node load monitors before timeouts occur. The service optimal allocation means is prepared to immediately reallocate services upon detecting execution status changes, reducing service interruption time and improving availability without requiring complex manual intervention structures
Solution Approach 2:
The continuous feedback loop from monitors to the allocation means enables prompt detection of service execution failures and immediate reallocation. This feedback mechanism reduces service interruption time by detecting failures before timeout and automatically reallocating services, thereby improving service availability while maintaining manageable system complexity
Data Source
AI summary
In a computer system executing a plurality of types of services, a service load monitor measures a load required to execute services in each of the computers. A node load monitor measures a load on each of the computers. A service optimal allocation machine determines an optimal computer and a service to be reallocated to the optimal computer, based on the measurement results of the service load monitor and the node load monitor, and reallocates the determined service to the optimal computer.