Traffic Aggregator Placement for Cost-Optimal Telecom Networks
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Solution Overview
Problem
Conventional network planning systems deploy aggregator units based on local site information, neglecting network-wide factors such as non-homogeneous resource demands and site-to-site transportation costs, leading to suboptimal cost configurations in telecommunication networks.
Innovation Solution
An optimization module collects network-wide information to determine a cost-optimal traffic aggregation configuration through a two-step optimization process, estimating the number of aggregator units needed and formulating decision variables and constraints to generate an aggregator placement map using an optimization solver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional network planning systems deploy aggregator units based on local site information, then deployment simplicity is maintained, but cost optimality deteriorates due to neglecting network-wide factors
Solution Approach 1:
The patent segments the network planning problem into two distinct phases: a network-wide aggregation phase that determines optimal aggregator placement across all sites, and local site configuration phases that implement those decisions at individual sites. This segmentation allows the system to incorporate network-wide cost factors while maintaining local deployment simplicity through standardized configuration templates.
Solution Approach 2:
The patent transitions from one-dimensional local site analysis to multi-dimensional network-wide optimization by incorporating additional dimensions such as inter-site transportation costs, aggregate resource demands across multiple sites, and hierarchical aggregation levels. This dimensional expansion enables cost-optimal placement decisions that consider the entire network topology rather than isolated site characteristics.
2Reliability
If aggregator units are placed to meet local resource demands, then local service requirements are satisfied, but network-wide transportation costs increase
Solution Approach 1:
The patent merges multiple local resource demand assessments into a unified network-wide aggregation analysis. By combining demand data from multiple sites and evaluating them collectively, the system identifies optimal aggregator placement locations that serve multiple sites efficiently, thereby reducing redundant transportation costs while maintaining adequate service levels at each location.
Solution Approach 2:
The patent changes the optimization parameters from purely local service-level metrics to a composite objective function that incorporates both service requirement satisfaction and network-wide transportation cost minimization. This parameter transformation enables the system to balance local reliability requirements with global cost efficiency through mathematical optimization.
3Quantity of substance
If network-wide optimization is implemented, then cost optimality improves, but computational complexity increases
Solution Approach 1:
The patent segments the complex network-wide optimization problem into manageable computational phases: data collection and aggregation, optimization model formulation, solver execution, and result decomposition for local implementation. This segmentation reduces computational complexity by breaking down the monolithic optimization problem into sequential processing stages that can be handled by standard optimization solvers.
Solution Approach 2:
The patent performs preliminary data aggregation and preprocessing steps before executing the main optimization calculation. By pre-processing network topology data, resource demand information, and cost parameters into standardized formats, the system reduces the computational burden on the optimization solver and accelerates the overall planning process.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for optimal placement of aggregator equipment in telecommunication networks. An embodiment operates by receiving, as an input, information corresponding to resource capacity of the one or more types of aggregator units and resource demands generated by a plurality of access nodes. The embodiment then calculates, based on the input, an optimized traffic aggregation configuration comprising an optimized group of one or more types of traffic aggregator units. Next, the embodiment modifies, based on the optimized traffic aggregation configuration, a network connectivity configuration corresponding to a plurality of network sites. Finally, the embodiment routes network traffic, via the optimized group of one or more types of traffic aggregator units, based on the modified network connectivity configuration.