Path computation based on dynamic performance monitoring systems and methods in optical networks
The present disclosure provides dynamic performance monitoring systems and methods for optical networks to ascertain optical network health in a flexible and accurate manner. The present invention introduces accurate estimations for optical channel performance characteristics based either on existing channels or with a dynamic optical probe configured to measure characteristics on unequipped wavelengths. Advantageously, the dynamic performance monitoring systems and methods introduce the ability to determine physical layer viability in addition to logical layer viability.
1. A method for path computation based on dynamic performance monitoring in an optical network, the method comprising:
obtaining dynamic performance monitoring data related to optical layer characteristics in the optical network;
performing an offline computation to generate a decision engine for determining physical validity of paths in the optical network based on the dynamic performance monitoring data, wherein the decision engine provides valid and reachable destinations from each source network element; and
disseminating the decision engine to network elements in the optical network for use in path computation at runtime.
2. The method of claim 1 , further comprising:
periodically repeating the obtaining, the performing, and the disseminating.
3. The method of claim 1 , wherein the decision engine is utilized in the path computation by a network element computing a path at runtime to determine physical validity of the path in addition to logical validity of the path.
4. The method of claim 1 , wherein the decision engine is one of a finite state machine, a rule-based database, and as a time-varying set of matrix constructs.
5. The method of claim 1 , further comprising:
computing offline a plurality of top candidate optical paths from each node to each other node based on a current snapshot of network resource usage; and
disseminating the plurality of top candidate paths to each of the network elements.
6. The method of claim 1 , wherein the dynamic performance monitoring data comprises feedback from real optical performance measurements in the optical network, and wherein the offline computation utilizes the real optical performance measurements in modeling and calculations to ensure optical path viability.
7. The method of claim 6 , wherein the real optical performance measurements are obtained from any of coherent transceivers, coherent probes, and coherent Optical Service Channels (OSCs).
8. The method of claim 1 , wherein the obtaining, the performing, and the disseminating is performed by a centralized server and the network elements operate a control plane with an individual network element utilizing the decision engine in path computation via the control plane.
9. A server adapted to perform path computation based on dynamic performance monitoring in an optical network, the server comprising:
a network interface and a processor communicatively coupled to one another; and
memory storing instructions that, when executed, cause the processor to
obtain via the network interface dynamic performance monitoring data related to optical layer characteristics in the optical network,
perform an offline computation to generate a decision engine for determining physical validity of paths in the optical network based on the dynamic performance monitoring data, wherein the decision engine provides valid and reachable destinations from each source network element, and
disseminate via the network interface the decision engine to network elements in the optical network for use in path computation at runtime.
10. The server of claim 9 , wherein the memory storing instructions that, when executed, further cause the processor to
periodically repeat the obtain, the perform, and the disseminate.
11. The server of claim 9 , wherein the decision engine is utilized in the path computation by a network element computing a path at runtime to determine physical validity of the path in addition to logical validity of the path.
12. The server of claim 9 , wherein the decision engine is one of a finite state machine, a rule-based database, and as a time-varying set of matrix constructs.
13. The server of claim 9 , wherein the memory storing instructions that, when executed, further cause the processor to
compute offline a plurality of top candidate optical paths from each node to each other node based on a current snapshot of network resource usage; and
disseminate the plurality of top candidate paths to each of the network elements.
14. The server of claim 9 , wherein the dynamic performance monitoring data comprises feedback from real optical performance measurements in the optical network, and wherein the offline computation utilizes the real optical performance measurements in modeling and calculations to ensure optical path viability.
15. The server of claim 14 , wherein the real optical performance measurements are obtained from any of coherent transceivers, coherent probes, and coherent Optical Service Channels (OSCs).
16. The server of claim 9 , wherein the network elements operate a control plane with an individual network element utilizing the decision engine in path computation via the control plane.
17. Software stored in one of volatile and non-volatile memory comprising instructions that, when executed, cause a processor to perform steps of:
obtaining dynamic performance monitoring data related to optical layer characteristics in the optical network;
performing an offline computation to generate a decision engine for determining physical validity of paths in the optical network based on the dynamic performance monitoring data, wherein the decision engine provides valid and reachable destinations from each source network element; and
disseminating the decision engine to network elements in the optical network for use in path computation at runtime.
18. The software stored in one of volatile and non-volatile memory of claim 17 , wherein the instructions that, when executed, further cause a processor to perform steps of:
periodically repeating the obtaining, the performing, and the disseminating.
19. The software stored in one of volatile and non-volatile memory of claim 17 , wherein the decision engine is utilized in the path computation by a network element computing a path at runtime to determine physical validity of the path in addition to logical validity of the path.
20. The software stored in one of volatile and non-volatile memory of claim 17 , wherein the decision engine is one of a finite state machine, a rule-based database, and as a time-varying set of matrix constructs.