Network Design System Optimizing Port and Device Cost
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional network design methods struggle to minimize power and cost effectively by failing to consider the interdependencies between route, line, and device configurations, leading to suboptimal arrangements that do not accurately account for the actual power consumption and operational costs of network devices.
Innovation Solution
A network design system that sets an objective function to minimize device cost, considering the number of ports and device candidates, and uses mathematical programming to determine the optimal arrangement of paths, devices, and ports, taking into account the relationship between the number of ports and device costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional manual design methods are used to arrange network devices and routes, then design flexibility and adaptability are maintained, but the ability to comprehensively consider dependencies among diverse design elements (route, line, device) is insufficient, leading to suboptimal power and cost minimization
Solution Approach 1:
The patent replaces manual mechanical design processes with an automated computer-based system that uses mathematical programming (mixed-integer linear programming) to optimize network configuration. The system automatically determines optimal routes, device placements, and port assignments by solving optimization problems, eliminating the need for manual consideration of complex dependencies while maintaining design quality.
Solution Approach 2:
The patent transforms the design problem into a mathematical optimization problem by defining objective functions (minimizing power consumption and cost) and constraint conditions (traffic demands, device capabilities, port availability). The system changes the approach from qualitative manual design to quantitative parameter optimization, using mathematical models to systematically explore design spaces and find optimal solutions.
2Measurement precision
If conventional methods minimize cost based on cost per port, then port-level optimization is achieved, but the actual device-level cost changes due to device replacement or configuration are not accurately captured
Solution Approach 1:
The patent merges port-level cost considerations with device-level cost implications into a unified optimization model. By formulating the problem as a mixed-integer linear programming problem, the system simultaneously optimizes port assignments and device configurations, capturing the interdependencies between ports and devices. This ensures that cost minimization accounts for both port-level and device-level factors, including replacement costs and configuration changes.
Solution Approach 2:
The optimization system serves multiple functions simultaneously: it determines optimal routes, selects appropriate devices, assigns ports, and calculates total cost. The unified mathematical model handles diverse design elements (routes, lines, devices) as interconnected variables, allowing the system to comprehensively consider all cost factors including device replacement, port allocation, and configuration requirements in a single optimization process.
3Reliability
If redundant lines and devices are arranged to accommodate traffic, then network reliability is improved, but power consumption and operating cost increase
Solution Approach 1:
The patent uses mathematical optimization to precisely control the parameters of network configuration (number of devices, type of devices, port assignments, route selection) to achieve the minimum necessary redundancy for traffic accommodation. The mixed-integer linear programming model calculates optimal configurations that provide sufficient reliability while minimizing power consumption, avoiding unnecessary redundant components and their associated energy costs.
Data Source
AI summary
An operator sets a path demand to be accommodated, and sets information of a device candidate, the number of ports, a path route and the like, which are demanded for a network, in an objective function that indicates a total cost when the path demand to be accommodated is newly included in the network. A mathematical programming problem for minimizing the objective function under a constraint condition derived from a configuration of the network is set, and a solution is obtained by using a solver for solving the mathematical programming problem. A device is added or the like to the network based on the obtained solution, and the demanded path is added to the network.