Service Deployment Control via Device Characteristic Analysis
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Solution Overview
Problem
In distributed computing systems, services are often not optimally deployed due to a lack of knowledge about the characteristics of users and devices, leading to sub-optimal service delivery, as creators or operators struggle to predict which services should be deployed together, especially when services belong to different domains.
Innovation Solution
A control node records user and device characteristics, determines dependent relationships between services and these characteristics, and controls service deployment on computer resources based on these relationships, grouping services for improved performance and user satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If services are deployed based on manual knowledge and predictions by creators or operators, then deployment control is simple and direct, but service deployment optimality deteriorates due to insufficient knowledge of service usage patterns and device characteristics
Solution Approach 1:
The system performs preliminary actions by recording device characteristics and service usage information before deployment decisions are made. The control node stores device characteristics (processor type, memory, screen resolution, operating system) and service usage patterns in advance, then uses this pre-collected data to automatically determine optimal deployment configurations, eliminating the need for manual prediction while maintaining simple deployment control.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring service usage information and device characteristics, then using this feedback to automatically adjust and optimize service deployment. The control node receives usage data, analyzes patterns, and dynamically determines deployment configurations based on actual service consumption patterns rather than manual predictions, improving deployment optimality while automating the process.
2Reliability
If services are deployed without considering device and user characteristics, then deployment process is simple and fast, but service quality deteriorates due to sub-optimal service delivery
Solution Approach 1:
The system applies local quality by tailoring service deployment to specific device characteristics and user profiles. The control node analyzes individual device attributes (processor type, memory, screen resolution, operating system) and service usage patterns to determine optimal deployment configurations for each device type or user group, ensuring high service quality for each local context while maintaining a standardized automated deployment process.
Solution Approach 2:
The system changes deployment parameters based on device characteristics and service usage patterns. The control node adjusts deployment configurations by varying parameters such as service placement, resource allocation, and deployment timing based on recorded device specifications and usage information, thereby improving service quality without requiring complex manual intervention for each deployment scenario.
3Productivity
If manual deployment control is used without automated analysis, then system complexity is low, but response time to service migration requests deteriorates due to insufficient knowledge for optimal deployment
Solution Approach 1:
The system implements self-service by enabling the control node to automatically analyze service usage patterns and device characteristics, then autonomously determine optimal deployment configurations without manual intervention. The control node independently processes service migration requests, queries stored device information, analyzes usage patterns, and executes deployment decisions automatically, achieving rapid service migration while maintaining manageable system complexity through automated rule-based decision-making.
Solution Approach 2:
The system performs preliminary actions by pre-recording and storing device characteristics and service usage information in databases before migration requests occur. This advance preparation enables the control node to quickly retrieve relevant data and make rapid deployment decisions when service migration requests are received, significantly improving migration speed while keeping the system relatively simple through structured data collection and automated rule-based analysis.
Data Source
AI summary
A method by a control node (100) is disclosed for controlling deployment of services on computer resources within a distributed computing system (110) for use by electronic devices (120). The method includes recording information (200) that identifies characteristics of the electronic devices (120) and/or users of the electronic devices (120) that are provided which of the services. Dependent relationships between the services and the characteristics of the electronic devices (120) and/or the characteristics of the users of the electronic devices (120) are determined (202) based on the information. Deployment of the services on the computer resources within the distributed computing system (110) is controlled (204) based on the identified relationships and for use by the electronic devices (120). Related control nodes, systems, and computer program products are disclosed.