Network Topology Optimization via Graph Theory
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Solution Overview
Problem
Legacy network infrastructure in underdeveloped communities and developing countries often results in hybrid network topologies that do not improve performance due to mismatched equipment speeds, bandwidths, and inefficient designs, leading to bottlenecks and congestion.
Innovation Solution
A system that uses a processor and computer-readable medium to probe networks, discover topologies, and apply graph theory to generate alternate designs that reduce latency, eliminate inefficient components, and optimize flow patterns, thereby improving network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If legacy network infrastructure is partially upgraded with recent equipment, then network performance is expected to improve, but hybrid network topologies are created that do not improve performance due to mismatched equipment speeds and bandwidths
Solution Approach 1:
The system discovers network topology characteristics including equipment speeds and bandwidths, then uses graph theory to optimize the network design by adjusting parameters such as the number of layers, hops, and loops to eliminate mismatches between legacy and new equipment capabilities
Solution Approach 2:
The patent introduces a new dimension of analysis by modeling the network as a graph structure and using mathematical optimization to find the optimal configuration, moving beyond traditional incremental upgrade approaches to achieve holistic network performance improvement
2Area of stationary object
If multiple layers of switches and routers are added to expand network coverage, then network capacity increases, but the number of hops and latency increase
Solution Approach 1:
The system optimizes network parameters by using graph theory to determine the minimum number of layers and hops required to achieve desired network coverage, eliminating unnecessary intermediate devices that contribute to latency while maintaining adequate coverage area
Solution Approach 2:
The patent creates an abstract graph model of the network that allows simulation and optimization of different configurations to find the optimal balance between coverage area and latency, avoiding the need to physically implement and test multiple network designs
3Loss of time
If network upgrades are implemented to reduce latency, then network performance improves, but the complexity of discovering and optimizing topology increases
Solution Approach 1:
The system performs self-service topology discovery by automatically probing the network and extracting topology characteristics without requiring manual intervention, then uses this discovered information to autonomously optimize the network design using graph theory algorithms
Solution Approach 2:
The patent implements a feedback mechanism where the system discovers current network topology, analyzes performance characteristics, generates optimized designs, and can iteratively improve the network based on measured outcomes, creating a continuous optimization loop
Data Source
AI summary
A system comprises a processor and a non-transitory computer-readable medium to store instructions for execution by the processor. The instructions are configured to discover a topology of a network in an on-premises datacenter, where the topology includes hardware and software components in the on-premises datacenter and in one or more hops from an external network to a gateway of the network. The instructions are configured to determine a plurality of parameters of the components that affect performance of applications and services running on the network. The instructions are configured to determine, based on the discovered topology and the parameters, an optimal topology for the network that optimizes one or more of the parameters to improve the performance of applications and services running on the network.