Workload Control Module for Mainframe Distributed Balance
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Solution Overview
Problem
There is a need to balance mainframe and distributed workloads effectively based on performance and cost considerations, as existing technologies lack real-time decision-making capabilities to allocate application workloads between these platforms optimally.
Innovation Solution
A processor collects performance and cost data from both mainframe and distributed computing platforms and allocates application workloads in real-time, breaking them into logical pieces and prioritizing platforms to balance performance and cost, using a workload control module that evaluates historical data and user inputs to determine the best platform for each workload unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If workload is allocated to mainframe platform, then processing performance and reliability are improved, but processing costs increase
Solution Approach 1:
The system dynamically allocates workload between mainframe and distributed platforms based on real-time performance metrics and cost data. The workload control module continuously monitors system state and adjusts allocation decisions, transitioning from static to dynamic resource management to optimize both reliability and cost efficiency.
Solution Approach 2:
The system changes allocation parameters by evaluating multiple factors including performance metrics, cost data, and workload characteristics. By adjusting these parameters in real-time, the system determines optimal platform selection for each workload unit, balancing reliability requirements against processing costs.
2Loss of energy
If workload is allocated to distributed computing platform, then processing costs are reduced, but performance may be compromised
Solution Approach 1:
The workload is segmented into individual workload units that can be independently allocated. This segmentation allows the system to distribute different units to appropriate platforms based on their specific requirements, enabling cost-effective allocation while maintaining overall performance through selective placement of critical tasks on the mainframe.
Solution Approach 2:
The system applies partial action by allocating only the necessary portion of workload to the mainframe platform based on performance requirements. Rather than allocating entire workloads, the system selectively assigns specific workload units to the mainframe when needed, reducing unnecessary costs while maintaining required performance levels.
3Productivity
If real-time workload allocation is implemented, then resource utilization is optimized, but system complexity increases
Solution Approach 1:
The workload control module serves as an intermediary that manages the complexity of real-time allocation decisions. It collects performance and cost data, evaluates workload units, and makes allocation decisions without requiring direct complex interactions between workload units and multiple platforms, thereby optimizing resource utilization while containing system complexity through centralized control.
Solution Approach 2:
The system implements feedback mechanisms by collecting real-time performance metrics and cost data from both platforms. This feedback loop enables the workload control module to continuously optimize allocation decisions based on actual system state, improving resource utilization while managing complexity through data-driven automated control.
Data Source
AI summary
In an approach for balancing mainframe and distributed workloads, a processor receives a request to allocate an application workload to a mainframe platform and a distributed computing platform. The application workload includes a plurality of work units. A processor collects performance and cost data associated with the application workload, the mainframe platform, and the distributed computing platform. A processor determines the mainframe platform and the distributed computing platform for the plurality of work units of the application workload, based on the analysis of the performance and cost data. A processor allocates the plurality of work units of the application workload to run on the mainframe platform and the distributed computing platform respectively to balance performance and cost in real time.