A method, an apparatus, and a system for time synchronization based on in-band telemetry are disclosed. The method includes: acquiring an estimated value of delay in a first transmission direction and an estimated value of delay in a second transmission direction; wherein the estimated value of delay in the first transmission direction is determined according to multiple delay samples in the first transmission direction, and the estimated value of delay in the second transmission direction is determined according to multiple delay samples in the second transmission direction, the first transmission direction is a direction from a second device to a first device, and the second transmission direction is vice versa; and determining a time system error of the first device relative to the second device according to the estimated value of delay in the first transmission direction and the estimated value of delay in the second transmission direction.

In an example, a Dynamic Host Configuration Protocol (DHCP) lease request from a client device connected to a network is received. Based on the DHCP lease request, an Internet Protocol (IP) address is assigned to the client device for a lease time. A first lease renewal request is received. A probability of utilization for a lease time block is predicted based on a historical lease pattern, device characteristics, traffic information, and DHCP information. Based on a combination of the probability of utilization and a reward value, the lease time block is allotted for lease renewal. For each allotment, the reward value is adjusted based on deployment characteristics and traffic load in the network, and a network connection duration of the client device. A normalized reward value for the lease time block is determined based on reward values for the lease time block over multiple allotments.

In an example, a Dynamic Host Configuration Protocol (DHCP) lease request from a client device connected to a network is received. Based on the DHCP lease request, an Internet Protocol (IP) address is assigned to the client device for a lease time. A first lease renewal request is received. A probability of utilization for a lease time block is predicted based on a historical lease pattern, device characteristics, traffic information, and DHCP information. Based on a combination of the probability of utilization and a reward value, the lease time block is allotted for lease renewal. For each allotment, the reward value is adjusted based on deployment characteristics and traffic load in the network, and a network connection duration of the client device. A normalized reward value for the lease time block is determined based on reward values for the lease time block over multiple allotments.

Disclosed herein is a method, a computer program product, and a carrier for indicating one-way latency in a data network (N) between a first node (A) and a second node (B), wherein the data network (N) lacks continuous clock synchronization, comprising: a pre-synchronisation step, a measuring step, a post-synchronisation step, an interpolation step, and generating a latency profile. The present invention also relates to a computer program product incorporating the method, a carrier comprising the computer program product, and a method for indicating server functionality based on the first aspect.

Techniques are disclosed for the identification of applications from communication sessions of network traffic between client devices and the generation of application-specific metrics for network traffic associated with the applications. In one example, a router obtains metrics for a plurality of packets. The router determines a session of a plurality of sessions associated with each packet. For each determined session, the router generates metrics for the session from the metrics of the packets associated with the session and determines an application of a plurality of applications associated with the session. For each determined application, the router generates metrics for the application from the metrics of the sessions associated with the application and transmits, to a device, the metrics for the application. In some examples, the router generates the metrics for each application on a per-client, per-next-hop, or per-traffic class basis.

Techniques are disclosed for the identification of applications from communication sessions of network traffic between client devices and the generation of application-specific metrics for network traffic associated with the applications. In one example, a router obtains metrics for a plurality of packets. The router determines a session of a plurality of sessions associated with each packet. For each determined session, the router generates metrics for the session from the metrics of the packets associated with the session and determines an application of a plurality of applications associated with the session. For each determined application, the router generates metrics for the application from the metrics of the sessions associated with the application and transmits, to a device, the metrics for the application. In some examples, the router generates the metrics for each application on a per-client, per-next-hop, or per-traffic class basis.

A network equipment monitoring analysis aid and guidance method, and its terminal device and readable storage medium are disclosed. The method is loaded into an equipment to execute the steps of collecting a history total traffic of a terminal device connected to the equipment; capturing a history time period traffic of each time period of the terminal device; analyzing the history total traffic and the history time period traffic by a quantitative analysis to generate a quantitative information of the terminal device; and presenting a corresponding guide information on a user interface according to the quantitative information. The guide information can be used to clearly mark a network traffic level of each terminal device in each time period and present it in a user interface, so as to visually present a network user's network activity behavior, guide parental use and monitoring, and set guidelines for members.

A network equipment monitoring analysis aid and guidance method, and its terminal device and readable storage medium are disclosed. The method is loaded into an equipment to execute the steps of collecting a history total traffic of a terminal device connected to the equipment; capturing a history time period traffic of each time period of the terminal device; analyzing the history total traffic and the history time period traffic by a quantitative analysis to generate a quantitative information of the terminal device; and presenting a corresponding guide information on a user interface according to the quantitative information. The guide information can be used to clearly mark a network traffic level of each terminal device in each time period and present it in a user interface, so as to visually present a network user's network activity behavior, guide parental use and monitoring, and set guidelines for members.

Apparatus including a network switch which includes switching circuitry to switch packets, packet drop decision circuitry to identify a packet that is to be dropped, packet duplication circuitry to duplicate the packet that is to be dropped, producing a first packet and a second packet, and packet exporting circuitry to export the first packet to a memory external to the switch via direct memory access (DMA). Related apparatus and methods are also provided.

A method includes causing, by a processor, a graphical user interface (GUI) to be output by a display. The GUI includes a first user input field identifying a target key performance indicator (KPI) associated with a network. A second user input field identifying a KPI peak-usage frequency. A third user input field identifying a peak-usage relationship. The method also includes creating a first monitoring profile based on the target KPI for the KPI peak-usage frequency for the peak-usage relationship. Storing the first monitoring profile. Monitoring the target KPI for the KPI peak-usage frequency based on the first monitoring profile. Collecting target KPI data over a period defined by the KPI peak-usage frequency. Determining a peak-usage during the period defined by the KPI peak-usage frequency based on the collected target KPI data. Periodically reporting peak-usage data based on the first monitoring profile.