Service Deployment Control System for IoT Value Chain Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data processing systems, particularly in the IoT context, face challenges in managing and optimizing data deployment across multiple stages of the value chain, as they are not designed to handle the full value chain efficiently, leading to suboptimal data processing and analysis.
Innovation Solution
A service deployment control system comprising a machine management module, network management module, service management module, and service deployment destination determination module, which dynamically selects the optimal deployment destination for data processing services based on resource requirements and communication costs across multiple stages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data processing services are deployed in multiple stages across different processes and sites, then the full value chain can be managed in a unified manner, but the deployment cost and system complexity increase
Solution Approach 1:
The patent segments the data processing system into multiple independent services that can be deployed across different processes and sites. Each service is a self-contained unit that can be independently managed, deployed, and scaled. This segmentation enables the full value chain to be managed in a unified manner while keeping individual service complexity manageable.
Solution Approach 2:
The patent creates a universal service deployment control system that can manage diverse data processing services across different processes and sites through a common platform. The system provides multi-functional capabilities including service registration, deployment destination determination, and cost calculation, enabling unified management of the full value chain without proportionally increasing complexity.
2Productivity
If data processing services are dynamically reconfigured based on operating environment, then productivity and efficiency improve, but the computational overhead and time for optimization increase
Solution Approach 1:
The patent performs preliminary actions by pre-registering services and pre-determining deployment destinations before actual data processing begins. The service deployment control system maintains a registry of available services and their characteristics, allowing for rapid deployment decisions without extensive real-time computation. This preliminary setup reduces the computational overhead during dynamic reconfiguration.
Solution Approach 2:
The patent implements feedback mechanisms where the service deployment control system continuously monitors operating conditions and adjusts service deployments based on this feedback. The system calculates deployment costs and determines optimal destinations by considering current system state, service requirements, and historical performance data, enabling efficient dynamic reconfiguration without excessive computational overhead.
3Reliability
If deployment cost calculation considers all subsequent stages, then overall optimization is achieved, but the computational complexity and processing time increase
Solution Approach 1:
The patent segments the multi-stage data processing system into distinct processes and sites, each with clearly defined service requirements and deployment constraints. The service deployment control system calculates deployment costs by considering each segment independently while accounting for inter-segment data flow and communication requirements. This segmented approach enables comprehensive optimization without overwhelming computational complexity.
4Productivity
If services are aggregated and distributed across multiple locations, then data utilization efficiency improves, but communication load and network complexity increase
Solution Approach 1:
The patent applies local quality by determining deployment destinations based on the specific characteristics of each service and the requirements of local processes and sites. Services are deployed to locations where they can most effectively utilize local data resources while minimizing communication with distant systems. The service deployment control system evaluates local data availability, processing capabilities, and communication costs to optimize service placement.
Solution Approach 2:
The patent merges services that have similar data requirements or communication patterns into the same deployment destination or process. By combining related services, the system reduces redundant communication and data transmission across the network. The service deployment control system identifies services that can be co-located or integrated, thereby reducing overall communication load while maintaining data utilization efficiency.
Data Source
AI summary
A service deployment control system includes a machine management module, a network management module, a service management module and a service deployment destination determination module. The machine management module is configured to acquire information on an operation of the service providing computer. The network management module is configured to acquire information on cooperation among a plurality of services. The service management module is configured to manage a condition for a computer resource that is set to and required for each of the services. The service deployment destination determination module is configured to select a service providing computer satisfying the condition for the computer resource required for the service out of the information on the operation as a candidate of a deployment destination of the service, generate combinations of the candidates as deployment patterns, calculate a deployment cost for each of the deployment patterns, select one of the deployment patterns.