Fibre Optic Network Design Using Infrastructure Optimization
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Solution Overview
Problem
Existing methods for designing fibre optic networks are laborious and inefficient, often requiring more infrastructure than necessary, and are not optimized for existing utility infrastructure, making them costly and time-consuming to design and modify.
Innovation Solution
A method that uses computational optimization to design fibre optic networks by reusing existing utility infrastructure such as power poles and ducts, minimizing the need for new construction by determining optimal geographic locations for nodes and arcs, thereby reducing construction costs and time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual design methods are used to ensure engineering requirements are met, then network reliability is improved, but design time and labor costs increase significantly
Solution Approach 1:
The patent replaces manual mechanical design processes with an automated computational system. The optimization algorithm automatically determines network topology, node locations, and arc routing by processing engineering requirements through software, eliminating manual labor while maintaining design quality and reliability standards.
Solution Approach 2:
The design system performs self-optimization by automatically evaluating multiple design scenarios and selecting the optimal configuration that meets engineering requirements. The algorithm independently adjusts network parameters and infrastructure placement without requiring manual intervention, enabling rapid iterative improvement of design solutions.
2Reliability
If manual design processes are used to meet physical requirements, then engineering standards are satisfied, but the resulting network includes more infrastructure than necessary, increasing construction costs
Solution Approach 1:
The optimization algorithm dynamically adjusts network design parameters including node density, arc routing, and infrastructure placement to find the minimum configuration that satisfies engineering requirements. By continuously varying these parameters and evaluating design outcomes, the system identifies the optimal balance between meeting standards and minimizing infrastructure quantity.
Solution Approach 2:
The system initially considers excessive infrastructure options and then systematically eliminates unnecessary elements through optimization. The algorithm evaluates designs with more infrastructure than needed and iteratively reduces the configuration to the minimal set that still satisfies all engineering requirements, thereby reducing construction costs.
3Device complexity
If existing utility infrastructure is not considered in network design, then design simplicity is maintained, but construction costs increase due to lack of infrastructure reuse opportunities
Solution Approach 1:
The optimization system integrates multiple infrastructure types (power poles, telecommunications ducts, street layouts) into a unified design framework. By treating different utility infrastructures as interchangeable resources that can serve multiple purposes, the algorithm identifies optimal reuse opportunities across various infrastructure networks, reducing construction costs without significantly increasing design complexity.
4Productivity
If manual modification of network design is performed to reduce infrastructure or adapt to changing requirements, then network optimization is achieved, but the modification process is laborious and time consuming
Solution Approach 1:
The design system is built to be dynamically adjustable, allowing rapid re-optimization when requirements change. The algorithm can quickly recalculate optimal network configurations in response to modified inputs such as new premises additions, changed bandwidth requirements, or updated infrastructure availability, enabling fast adaptation without manual redesign efforts.
Data Source
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AI summary
A system and method of designing a fibre optic network for a plurality of premises in a geographic area that has existing infrastructure comprising electronically generating design outputs by optimising geographic locations of the nodes and arcs in the fibre optic network using fibre optic network design inputs and existing infrastructure inputs whereby said design outputs comprise the optimised geographic locations of said nodes and said arcs in the fibre optic network relative to said existing infrastructure, and electronically outputting the design outputs.