Abstract: Aspects of the subject disclosure may include, for example, a processing system that performs operations including collecting encrypted network traffic flow data from user interaction with an application, deriving a first set of traffic feature vectors from the encrypted network traffic flow data collected, training a machine learning algorithm on the first set of traffic feature vectors to classify each traffic feature vector in the first set of traffic feature vectors as associated with a type of the application or not associated with the type of the application, and classifying whether an encrypted network traffic flow as the type of the application by applying the machine learning algorithm to a traffic feature vector of the encrypted network traffic flow. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a processing system that performs operations including collecting encrypted network traffic flow data from user interaction with an application, deriving a first set of traffic feature vectors from the encrypted network traffic flow data collected, training a machine learning algorithm on the first set of traffic feature vectors to classify each traffic feature vector in the first set of traffic feature vectors as associated with a type of the application or not associated with the type of the application, and classifying whether an encrypted network traffic flow as the type of the application by applying the machine learning algorithm to a traffic feature vector of the encrypted network traffic flow. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a processing system that performs operations including collecting encrypted network traffic flow data from user interaction with an application, deriving a first set of traffic feature vectors from the encrypted network traffic flow data collected, training a machine learning algorithm on the first set of traffic feature vectors to classify each traffic feature vector in the first set of traffic feature vectors as associated with a type of the application or not associated with the type of the application, and classifying whether an encrypted network traffic flow as the type of the application by applying the machine learning algorithm to a traffic feature vector of the encrypted network traffic flow. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a processing system that performs operations including collecting encrypted network traffic flow data from user interaction with an application, deriving a first set of traffic feature vectors from the encrypted network traffic flow data collected, training a machine learning algorithm on the first set of traffic feature vectors to classify each traffic feature vector in the first set of traffic feature vectors as associated with a type of the application or not associated with the type of the application, and classifying whether an encrypted network traffic flow as the type of the application by applying the machine learning algorithm to a traffic feature vector of the encrypted network traffic flow. Other embodiments are disclosed.

Abstract: A system for managing one or more service level agreements associated with a switched metro Ethernet network is disclosed and manages one or more service level agreements associated with a switched metro Ethernet network. The system also includes a service level agreement (SLA) management reporting system (MRS) and a performance engine (PE) data filter coupled to the SLA-MRS. Further, the system includes one or more network elements connected to the PE data filter, wherein the SLA-MRS is configured to receive performance data from the PE data filter and at least partially based on the performance data validate one or more customer claims regarding an SLA violation.

Abstract: A method for monitoring a network includes determining at least one of a jitter value or a delay value of a network connection between a source switch and a destination switch of the network. The method further includes determining a packet delivery rate value for each network segment of a sequence of one or more network segments connecting the source switch and the destination switch, each network segment comprising two switches, wherein at least one of the two switches is connected to one of a switch of another network segment, the source switch, or the destination switch. The method additionally includes determining an overall packet delivery rate value based on the one or more packet delivery rate values determined for each network segment of the sequence of one or more network segments.

Abstract: Method of collecting data from one or more network elements used to support customer networks. The method may include compiling a customer list from information extracted from a customer information database and an operation processes database. The customer list may be used to indicate one or more customers, the network elements associated therewith, and network addresses for each of the listed network elements. The method may include automatically generating data collection messages to the network addresses specified in the customer list.

Abstract: A system for managing one or more service level agreements associated with a switched metro Ethernet network is disclosed and manages one or more service level agreements associated with a switched metro Ethernet network. The system also includes a service level agreement (SLA) management reporting system (MRS) and a performance engine (PE) data filter coupled to the SLA-MRS. Further, the system includes one or more network elements connected to the PE data filter, wherein the SLA-MRS is configured to receive performance data from the PE data filter and at least partially based on the performance data validate one or more customer claims regarding an SLA violation.

Abstract: A method for monitoring a network includes determining at least one of a jitter value or a delay value of a network connection between a source switch and a destination switch of the network. The method further includes determining a packet delivery rate value for each network segment of a sequence of one or more network segments connecting the source switch and the destination switch, each network segment comprising two switches, wherein at least one of the two switches is connected to one of a switch of another network segment, the source switch, or the destination switch. The method additionally includes determining an overall packet delivery rate value based on the one or more packet delivery rate values determined for each network segment of the sequence of one or more network segments.

Abstract: Method of collecting data from one or more network elements used to support customer networks. The method may include compiling a customer list from information extracted from a customer information database and an operation processes database. The customer list may be used to indicate one or more customers, the network elements associated therewith, and network addresses for each of the listed network elements. The method may include automatically generating data collection messages to the network addresses specified in the customer list.

Abstract: A system for converting autonomous performance monitoring (PM) data into periodic PM data in a network includes a server, a data collector electrically coupled to the server, a plurality of network elements (NEs) electrically coupled to the data collector, and a user database electrically coupled to the server. When connectivity of the system has been established for at least a predetermined time duration, and a new value for a signal related to at least one of system performance monitoring, fault monitoring and configuration management has been presented autonomously during the predetermined time duration by at least one of the NEs, the data collector presents the new value to the server, and the server tags the new value with the time for the end of the predetermined interval and presents the tagged new value to at least one user application in the user database.

Abstract: A method for monitoring a network includes injecting a plurality of data packets into the network. The data packets are transmitted between a source device and a destination device. A plurality of reflected data packets is collected. The plurality of reflected data packets are reflected from the destination device to the source device. Also, the plurality of reflected data packets includes at least a portion of the data packets injected into the network. The method further includes determining a total number of the reflected data packets. A packet delivery rate, a latency value, and a jitter value can be calculated based at least partially on the total number of reflected data packets. Further, the packet delivery rate, the latency value, and the jitter value can be reported to a user.

Abstract: A network capacity management system and method are disclosed. In one form, a capacity management system for use with an optical network includes a network capacity management engine operable to actively access a network element. The system further includes a network-based application interface associated with the network capacity management engine. The application may facilitate providing information associated with a network element to a user in near real-time.