Management Server for Distributed Processing Resource Allocation
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Solution Overview
Problem
Conventional distributed processing systems face challenges in efficiently utilizing calculation resources quickly and at low cost, particularly due to the high cost of preparing multiple servers and the need for rapid deployment of resources for large-scale numerical calculations.
Innovation Solution
A distributed processing system that includes a management server and multiple nodes connected via a network, where the management server decomposes tasks into jobs, allocates them to available nodes based on resource availability, communication speed, and network distance, and summarizes results for efficient resource utilization, allowing nodes to participate voluntarily and withdraw when tasks are completed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a large number of servers are prepared for distributed processing, then processing speed and resource utilization are improved, but cost increases significantly
Solution Approach 1:
The patent creates virtual copies of server resources through containerization technology. Instead of preparing multiple physical servers, the system creates virtualized instances that can be rapidly deployed and scaled. These virtual server copies share underlying hardware resources while providing isolated processing environments, thus improving processing speed without proportionally increasing the number of physical servers.
Solution Approach 2:
The patent designs a multi-functional platform that can serve multiple purposes: distributed processing, data analytics, and various computational tasks. By making the server infrastructure universal and adaptable to different workloads, the system maximizes the utilization of existing servers, reducing the need to prepare additional servers for specific processing demands.
2Adaptability or versatility
If multiple servers are prepared for distributed processing, then calculation resource availability is improved, but deployment time and complexity increase
Solution Approach 1:
The patent pre-configures container images and processing environments before they are needed. These virtualized resource templates are prepared in advance with all necessary software, libraries, and configurations already in place. When processing demands arise, these pre-configured resources can be rapidly instantiated and deployed without requiring complex setup procedures at deployment time.
Solution Approach 2:
The system implements automated resource provisioning and management where the platform itself handles the complex tasks of resource allocation, configuration, and orchestration. The self-service mechanism automatically discovers available resources, configures appropriate processing environments, and manages workload distribution without requiring manual intervention, thus reducing deployment complexity while maintaining high resource availability.
3Productivity
If calculation resources are monitored and allocated dynamically, then resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements a feedback-based resource management system that continuously monitors resource utilization metrics such as CPU usage, memory consumption, and processing queue depth. Based on this real-time feedback, the system dynamically adjusts resource allocation decisions, scaling processing capacity up or down according to actual demand. This feedback loop enables high resource utilization efficiency while the automated nature of the control reduces the perceived system complexity for users.
Solution Approach 2:
The system employs dynamic resource allocation where processing resources are not statically assigned but flexibly adjusted based on workload characteristics. The platform can dynamically provision new container instances, migrate workloads between resources, and adjust processing priorities in real-time. This dynamic approach maximizes resource utilization efficiency while the automated orchestration manages the complexity of coordinating these dynamic changes.
Data Source
AI summary
A management server includes processing circuitry configured to accept a task that is a request for calculation by a distributed processing system from a terminal device, decompose the task into a plurality of jobs, determine, from calculation resources available for calculation servers obtained in advance from the calculation servers, respectively, a schedule of the jobs to be allocated to the calculation servers, transmit, based on the schedule, the jobs to be allocated to the calculation servers, respectively, accept calculation results of the jobs from the calculation servers, respectively, generate a calculation result of the task based on the accepted calculation results of the jobs, and transmit the calculation result of the task to the terminal device.