Network Graph Edge Scoring for Communication Routing
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Solution Overview
Problem
Determining optimal routes in optical communication networks is challenging due to the NP-hard nature of the problem, leading to intractability as network size and demands increase, and existing methods fail to effectively prioritize communication links based on topology and characteristics.
Innovation Solution
A method that uses edge scores determined by graph cuts and communication link characteristics to configure communication networks, prioritizing lower-priority links and preserving topologically important links for backup use, implemented through a network management system that calculates scores based on centrality and availability, and updates weights in response to network changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional routing methods are used to determine optimal paths in communication networks, then the problem becomes intractable as network size and number of demands increase, but the routing efficiency and service quality deteriorate
Solution Approach 1:
The patent transforms the routing problem from finding optimal paths directly to finding paths with minimum edge scores. The edge score is a composite parameter that combines graph cut rank (topological importance) and communication link characteristics (bandwidth, delay, cost). This parameter transformation makes the NP-hard problem tractable by providing a clear scoring metric for path selection.
Solution Approach 2:
The patent segments the network evaluation into two independent components: graph cut analysis (topological structure) and communication link characteristics (physical properties). This segmentation allows each component to be evaluated separately and combined into a composite edge score, simplifying the overall routing decision process.
2Reliability
If all communication links are treated equally in routing decisions, then the routing process is simple, but network resilience and capacity utilization deteriorate
Solution Approach 1:
The patent applies local quality by assigning different scores to different edges based on their specific topological importance and communication characteristics. Instead of treating all links uniformly, each edge receives a customized score reflecting its local properties, enabling differentiated routing decisions that enhance network resilience.
Solution Approach 2:
The edge score acts as an intermediary metric that mediates between topological importance (graph cut rank) and communication link characteristics. This intermediary transformation allows the routing algorithm to balance multiple factors without directly comparing incompatible metrics, simplifying the decision-making process while improving reliability.
3Productivity
If topologically important links are used for all demands, then routing efficiency is maximized, but network resilience deteriorates due to lack of backup capacity
Solution Approach 1:
The patent introduces dynamics by making the effective cost of edges dynamic based on demand patterns and network state. The scoring mechanism allows the network to adaptively route different demands through different paths, balancing efficiency and resilience. Topologically important links may be used for some demands while preserving capacity for backups, creating a dynamic balance.
Data Source
AI summary
A network management system can be configured to identify routes for satisfying a set of demands on a communications network using a network graph that represents the communication network. The network graph edges can have edge scores that indicate a priority of the edge. The edge score for a network edge corresponding to a communication link in the communication network can depend on the topology of the communication network or the characteristics of the communication link. The network management system can iteratively identify candidate path(s) on the network graph that correspond to each of the demands and determine a score for each candidate path using the edge scores. In each iteration, the network management system can select the lowest score candidate path, update the network graph to reflect the selection of this candidate path, update the edge scores based on the updating of the network graph, and update the candidate paths for the remaining demands as needed.