Ciena

About: Ciena is a company organization based out in Hanover, Maryland, United States. It is known for research contribution in the topics: Signal & Node (networking). The organization has 1259 authors who have published 1557 publications receiving 25989 citations.

Optical cross connect synchronization architecture and method

Abstract: A synchronization architecture for a cross connect switch having an ingress stage, a center stage, and an egress stage utilizes optical interfaces and media to distribute a system clock and frame sync to the I/O modules and switch fabric so that system can reassign the source/destination of the numerous STS-1 streams. A main synchronization module encodes the frame sync within the system clock. An optical interface converts the encoded sync signal to an optical sync signal which is sent over optical media to a secondary synchronization module which extracts the encoded frame sync from the optical sync signal and recovers the system clock. The system clock may be frequency multiplied or divided as necessary for distribution to the ingress and egress switch fabrics as well as the I/O modules. The sync reference may be externally provided or derived from an optical input data signal and forwarded to the main sync module using an optical pathway.

Systems and methods for communication system control utilizing corrected forward error correction error location identifiers

Abstract: The present invention provides systems and methods for communication system control utilizing corrected forward error correction (FEC) error location identifiers in multi-level modulation scheme systems. The present invention utilizes precise error correction information, available for each FEC block of a particular code (including, but not limited to, block codes and concatenated block codes employing iterative decoding as well as convolutional codes (including turbo codes) and low-density parity-check code (LDPC) class codes) used (e.g., Bose, Ray-Chaudhuri, Hocquenghem (BCH), Reed-Solomon, etc.), as a result of the FEC decoding process to provide feedback to close the loop for control of a demodulator (i.e., receiver). Each error location can be uniquely traced back to a particular sub-rate signal path, with running, post-FEC corrected BER (bit error rate) calculations generated on each sub-rate signal. Advantageously, this provides the ability to adjust thresholds and various other parameters to achieve and maintain error-free operation quickly.

Optimal Node Hardware Module Planning for Layer-One Optical Transport Networks

Abstract: Most of the existing studies on traffic grooming focus on minimizing required network link capacity and providing a serving relationship between client services and link capacity. Subsequent to this step, it is important to plan for actual client service add/drop over client service ports and end-to-end lightpath establishment over network ports, which is, however, not well investigated. We call such an effort node hardware module planning. This is an industrially practical problem aiming to minimize the node hardware cost since hardware modules are usually the most expensive in a network. Based on a link-based traffic grooming result, we develop a mixed integer linear programming (MILP) model to optimally plan hardware modules. To overcome the computational difficulty of the MILP model under large-size planning scenarios, we also develop a fast suboptimal heuristic for hardware module planning. Simulation studies indicate that the heuristic is efficient to realize a design close to an optimal solution obtained by the MILP model for both of the single-hop and multi-hop grooming modes. Also, the multi-hop grooming mode requires not only fewer link capacity units than the single-hop mode as found in most of the existing studies, but also lower node hardware costs. Finally, the evaluation of the impact of the switch backplane size shows that given a certain set of hardware modules, a saturated switch backplane size exists after which a further increase of the backplane size will not bring further reduction of the network hardware cost.

Local span mesh restoration (LSMR)

Abstract: An embodiment of the invention provides a method and apparatus for restoring a connection in a network. The connection is typically a sub network connection (SNC). In an embodiment, a failed line in a link connecting a first node and a second node is detected, where the failed line is associated with a sub network connection (SNC). The sub network connection (SNC) is then mapped to an alternate line in the link. The first node will change cross connections in a switch fabric in the first node, while the second node will change cross connections in a switch fabric in the second node, so that both nodes can transmit data on the selected alternate line, in order to restore the SNC.

Traffic-adaptive network control systems and methods

Abstract: Traffic-adaptive network control systems and methods for a network, implemented by a server, include monitoring data associated with the network; generating a traffic forecast based on the monitored data; generating a schedule of actions based on a comparison of the traffic forecast to observed data; and causing orchestration of the actions in the network based on the generated schedule. The network can include a Software Defined Networking (SDN) network.