Fiber Network Design System Using DFN Algorithms
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Solution Overview
Problem
Conventional methods for fiber network planning rely on construction-led approaches, making it challenging to achieve optimized fiber rollout management, especially in dynamic environments where deviations in design are not effectively updated, leading to inefficient network planning and high initial costs.
Innovation Solution
A design and engineering-led method and system that utilizes geocoded addresses, Average Revenue Per User (ARPU), and Distributed Fiber Network (DFN) algorithms to compute fiber rollout cost projections, select suitable fiber technologies, and generate optimized fiber networks connecting maximum users with minimum cost, incorporating AutoCAD for construction design and digital reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional construction-led approach is used for fiber network planning, then field survey and construction can be performed, but optimized network planning is challenging and initial rollout cost is high
Solution Approach 1:
The patent inverts the conventional construction-led approach by implementing a design-led approach. Instead of starting with field survey and construction then planning, the system first performs comprehensive network planning using graph theory algorithms to optimize the fiber route, calculates precise material requirements, and then executes construction based on this optimized design. This inversion resolves the contradiction by achieving optimized planning while maintaining construction feasibility.
Solution Approach 2:
The patent applies preliminary action by performing all network planning calculations, route optimizations, and material requirement computations before actual construction begins. The system pre-calculates the optimal fiber paths, determines exact duct and cable quantities, and prepares comprehensive construction plans in advance, eliminating the need for complex on-site decision-making during construction.
2Productivity
If conventional graph theory methods are used for fiber network planning, then network design can be performed, but finding an optimized network planning is challenging
Solution Approach 1:
The patent transforms the network planning problem by changing the mathematical parameters and algorithms used. Instead of conventional graph theory methods, the system employs advanced optimization algorithms that incorporate multiple parameters including fiber attenuation, duct capacity constraints, terrain characteristics, and material costs. This parameter transformation enables precise optimization of network planning while maintaining computational efficiency.
Solution Approach 2:
The patent replaces conventional manual or simple automated planning methods with a sophisticated computer-based optimization system. The system uses algorithms that automatically calculate optimal routes, evaluate multiple design scenarios, and determine precise material requirements, substituting complex manual calculations and iterative design processes with automated computational methods that achieve both high productivity and precision.
3Adaptability or versatility
If there is deviation in planned design, then field conditions may require changes, but conventional methods fail to update the deviation in design dynamically
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor construction progress and compare actual field conditions with the planned design. When deviations are detected, the system automatically updates the network plan, recalculates material requirements, and adjusts the optimization parameters. This real-time feedback loop maintains design flexibility while preventing information loss by ensuring the plan always reflects current field conditions.
Solution Approach 2:
The patent transforms the static conventional design process into a dynamic system that can adapt to changing field conditions. The network plan is not fixed but can be continuously updated and re-optimized based on actual construction progress, terrain variations, and emerging requirements. This dynamic approach maintains adaptability while preserving complete design information through automated update mechanisms.
4Quantity of substance
If maximum user connectivity is achieved, then more users are connected, but fiber rollout cost increases
Solution Approach 1:
The patent optimizes the balance between user connectivity and rollout cost by transforming the optimization parameters. The system incorporates cost-weighted algorithms that evaluate multiple routing options, selecting paths that maximize the number of connected users per unit cost. It dynamically adjusts design parameters such as fiber strand count, duct sharing arrangements, and route selection to achieve optimal cost-efficiency ratios while maximizing user connectivity.
Solution Approach 2:
The patent applies multi-functionality by designing the fiber network to serve multiple purposes simultaneously. The optimized routes are designed to connect multiple users along a single path, enabling one fiber deployment to serve numerous customers. The system identifies and exploits opportunities where a single duct or cable can provide service to multiple locations, maximizing user connectivity while minimizing total rollout cost.
Data Source
AI summary
Optical fiber network or fiber network is used for transmitting large volumes of data with maximum speed. Fiber to home is a recent technology of the fiber network where the initial fiber rollout cost is more. Hence a proper network management is necessary to rollout the fiber network in an optimized manner. Conventional methods provides construction led approach for fiber network planning and field survey. The present disclosure receives a plurality of geocoded addresses associated with a plurality of users and an average revenue per user. A fiber rollout cost projection is performed based on the input data and a fiber network is generated based on the projected fiber rollout cost. Further, field survey is performed based on the generated network and a fiber network construction design is made. Further, a fiber network rollout is performed based on the fiber network construction design and a redline deviation markup.