Network Topology Identification via Binary Decision Tables
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Solution Overview
Problem
As communication networks experience increased bandwidth demands, identifying and managing network topologies becomes complex due to varying combinations of routers and potential node failures, leading to bottlenecks and challenges in ensuring service level agreement (SLA) compliance.
Innovation Solution
The use of Binary Decision Tables to analyze and identify network topologies by determining valid combinations of network nodes, generating performance measurement commands, and calculating performance metrics, ensuring accurate and reliable end-to-end path topologies and compliance with SLA requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If larger, more capable routers are used to increase bandwidth capacity, then throughput increases, but device complexity and cost increase
Solution Approach 1:
The network is segmented into multiple paths between source and destination nodes. Instead of relying on a single high-capacity router, traffic is divided and routed through multiple smaller routers in parallel paths, achieving high throughput while reducing the complexity of individual devices.
Solution Approach 2:
Multiple smaller routers are configured to perform multiple functions - each router can handle traffic for different paths and serve as backup for others. This multi-functionality allows the network to achieve high throughput capacity without requiring each individual router to be overly complex.
2Productivity
If more network nodes are added to increase bandwidth capacity, then throughput increases, but the number of possible topologies and measurement combinations increases exponentially
Solution Approach 1:
The exponential set of all possible topologies is segmented into a hierarchical structure of source nodes, intermediate nodes, and destination nodes. This segmentation allows the system to focus on measuring only the relevant active paths rather than analyzing all possible topology combinations.
Solution Approach 2:
From the complete set of all possible network topologies, the system extracts and identifies only the active topologies that are currently in use. This extraction process reduces the measurement burden from exponential complexity to a manageable subset of relevant configurations.
3Reliability
If comprehensive performance measurement of all network paths is implemented, then reliability of SLA compliance increases, but measurement time and resource consumption increase
Solution Approach 1:
The system performs preliminary identification and classification of active network topologies before conducting performance measurements. By pre-determining which topologies are actually in use, the system avoids wasting measurement time on inactive paths while ensuring all active paths are measured for SLA compliance.
Solution Approach 2:
Instead of measuring all possible network paths (excessive action), the system measures only the active topologies that are currently in use (partial action). This partial measurement approach maintains SLA compliance reliability while significantly reducing the time and resources required compared to comprehensive measurement of all possible paths.
Data Source
AI summary
Methods and apparatus to identify network topologies are disclosed. An example method includes determining a set of network nodes in a set of end-to-end communication paths between a pair of designated nodes based on a configuration of the network and locations of the designated nodes within the network. The set of network nodes excludes a subset of the network nodes that are present in all the end-to-end communication paths. A binary decision table is generated that includes up to 2.sup.N entries where N is the number of nodes in the set of network nodes. The respective nodes are represented in respective columns of the binary decision table, and data in the row of the columns indicates distinct combinations of the network nodes. Performance measurement commands are generated for a set of valid combinations of the network nodes that enable monitoring of the network according to the configuration of the network.