Loopback Detection Beacon for Network Loop Analysis
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Solution Overview
Problem
Current technologies fail to effectively detect and manage loopbacks and network loops in networks, leading to issues like loss of connectivity, MAC address learning interference, and increased traffic, which can cause network disruptions.
Innovation Solution
The method involves using loopback detection beacons (LPDBs) and network loop detection beacons (NLDBs) to identify and differentiate between various types of loopbacks by monitoring for specific protocol data unit information, timestamps, and service specifications, allowing for timely fault location and remediation with minimal disruption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If loopback detection beacons are sent and monitored to detect loopbacks, then detection accuracy is improved, but network traffic increases and complexity increases
Solution Approach 1:
The patent introduces loopback detection beacons (LPDBs) as intermediary packets that carry specific identifiers and timestamps. These beacons act as mediators between network devices to enable loopback detection without requiring complex continuous monitoring mechanisms. The beacons simplify the detection process by providing discrete, identifiable signals that can be easily tracked across network segments.
Solution Approach 2:
The patent creates simplified copies of network traffic patterns using LPDBs. Instead of analyzing actual data traffic for loopback conditions, the system sends simplified beacon packets that replicate the essential detection function. These beacon copies contain reduced information (identifiers, timestamps) compared to full data packets, making them easier to process while maintaining detection capability.
2Measurement precision
If loopback detection beacons are sent and monitored to detect loopbacks, then detection accuracy is improved, but network traffic increases
Solution Approach 1:
The patent employs disposable loopback detection beacons that are sent as discrete packets and then discarded. Each beacon is a short-lived object that performs its detection function and is then removed from the network. This approach minimizes persistent traffic overhead compared to continuous monitoring mechanisms, as beacons are only present during the brief detection window and are not required to remain in circulation.
Solution Approach 2:
The patent extracts essential detection information from complex network traffic analysis by using simplified beacon packets. Instead of processing entire data streams for loopback conditions, the system extracts and transmits only the critical detection parameters (identifiers, timestamps) within LPDBs. This extraction reduces the quantity of data needing to be processed while maintaining detection accuracy.
3Reliability
If monitoring is performed for a predetermined time period to detect LPDBs, then detection reliability is improved, but time consumption increases
Solution Approach 1:
The patent implements preliminary action by setting a predetermined time period before actual detection occurs. The system prepares monitoring parameters and time windows in advance, allowing for efficient detection when beacons arrive. This preliminary setup ensures reliable detection while minimizing actual monitoring time, as the time period is predetermined rather than continuously open-ended.
Solution Approach 2:
The patent employs periodic action through the use of predetermined time periods for monitoring. Instead of continuous monitoring, the system uses periodic detection windows defined by the predetermined time periods. This periodic approach maintains reliability by ensuring beacons are detected within expected timeframes while reducing overall time consumption by limiting monitoring to specific intervals rather than continuous operation.
Data Source
AI summary
A method of determining the presence of a loopback in one or more networks comprises storing information related to a test instance; sending a loopback detection beacon (LPDB) containing information related to the test instance from a port on an originating device; monitoring the port for a predetermined time period to detect LPDBs arriving at the port during the predetermined time period; and determining whether a detected LPDB contains information corresponding to the stored information, to detect the presence of a loopback. The method may determine whether a detected loopback is a port loopback, a tunnel loopback or a service loopback. The stored information related to the test instance may be deleted if an LPDB arriving at the port and containing information corresponding to the stored information is not detected within the predetermined time period.