A switch is provided for routing packets in an interconnection network. The switch includes a plurality of egress ports to transmit packets. The switch also includes one or more ingress ports to receive packets. The switch also includes a port and bandwidth capacity circuit configured to obtain (i) port capacity for a plurality of egress ports of the switch, and (ii) bandwidth capacity for transmitting packets to a destination. The switch also includes a network capacity circuit configured to compute network capacity, for transmitting packets to the destination, via the plurality of egress ports, based on a function of the port capacity and the bandwidth capacity. The switch also includes a routing circuit configured to route one or more packets received via one or more ingress ports of the switch, to the destination, via the plurality of egress ports, based on the network capacity.

Example aspects include techniques for implementing resource governance in multi-tenant environment. These techniques may include receiving a service request for a multi-tenant service from a client device, and predicting a resource utilization value (RUV) resulting from execution of the service request based on text of the service request, an amount of data associated with the client device at the multi-tenant service, and/or a temporal execution value. In addition, the techniques may include determining that the RUV is greater than a preconfigured threshold identifying an expensive request, and applying a load balancing strategy to the service request based on the RUV being greater than the preconfigured threshold.

Disclosed are systems and methods for a robust Self-Organizing Network (SON) framework that quantifies SON applications' control and management of a network into key performance indicators (KPI) that are leveraged to determine the impact of a SON's application effectiveness in regulating network parameters, which then dictates how the SON application operates. The disclosed framework is configured to receive multiple data streams from existing data sources, determine the performance of a node on a network, and then automatically perform SON operations based therefrom. The disclosed framework can utilize this information to predict additional and/or future opportunities for SON automation on the network.

Some embodiments provide a method for providing redundancy and fast convergence for modules operating in a network. The method configures modules to use a same anycast inner IP address, anycast MAC address, and to associate with a same anycast VTEP IP address. In some embodiments, the modules are operating in an active-active mode and all nodes running modules advertise the anycast VTEP IP addresses with equal local preference. In some embodiments, modules are operating in active-standby mode and the node running the active module advertises the anycast VTEP IP address with higher local preference.

The method of some embodiments samples data flows. The method samples a first set of flows during a first time interval using a first logical port window for the first time interval. The first logical port window identifies a first set of non-contiguous layer 4 (L4) values in an L4 port range that are candidate values for sampling the flows during the first time interval. The method also samples a second set of flows during a second time interval using a second logical port window for the second time interval. The second logical port window identifies a second set of non-contiguous L4 values in an L4 port range that are candidate values for sampling the flows during the second time interval.

Embodiments described herein provide systems and methods for reference signal configuration for multiple panels with panel-specific channel state information reference signals (CSI-RS) configurations and quasi-collocation (QCL) indication, including QCL type definition and indication for panel-specific CSI-RS configurations. Exemplary embodiments further provide multi-component precoder structure with panel specific component precoder and panel common precoder. Embodiments include: (semi)-open-loop schemes using random precoding for panel common precoder and/or panel specific precoder; panel selection/restriction with panel common precoder; MU-MIMO operation using different set of panels; and panel-wise CSI reporting.

An apparatus includes an input interface to receive incoming packets from a first network device and an output interface to send outgoing packets to a second network device. Media access control security (MACsec) circuitry is coupled between the input interface and the output interface. Bypass flow-control (FC) circuitry is coupled between the input interface and the MACsec circuitry. The bypass FC circuitry is to detect an FC packet in the incoming packets and pass the FC packet passively to the output interface to enable end-to-end flow control directly between the first network device and the second network device.

Facilitating localization of faults in core, edge, and access networks is provided herein. Operations of a system can include establishing a restoration of a group of communication paths of a network infrastructure that includes network nodes between a root network node and a leaf network node. A fault is determined to exist in the group of communication paths between the root network node and the leaf network node. The operations also can include determining that a defined network node of the network nodes is a source of the fault based on respective positions of user equipment experiencing the fault relative to the defined network node. Further, the operations can include removing the fault based on controlling a functionality of the defined network node.

Techniques for dynamically load balancing traffic based on predicted and actual load capacities of data nodes are described herein. The techniques may include determining a predicted capacity of a data node of a network during a period of time. The data node may be associated with a first traffic class. The techniques may also include determining an actual capacity of the data node during the period of time, as well as determining that a difference between the actual capacity and the predicted capacity is greater than a threshold difference. Based at least in part on the difference, a number of data flows sent to the data node may be either increased or decreased. Additionally, or alternatively, a data flow associated with a second traffic class may be redirected to the data node during the period of time to be handled according to the first traffic class.

Techniques for dynamically load balancing traffic based on predicted and actual load capacities of data nodes are described herein. The techniques may include determining a predicted capacity of a data node of a network during a period of time. The data node may be associated with a first traffic class. The techniques may also include determining an actual capacity of the data node during the period of time, as well as determining that a difference between the actual capacity and the predicted capacity is greater than a threshold difference. Based at least in part on the difference, a number of data flows sent to the data node may be either increased or decreased. Additionally, or alternatively, a data flow associated with a second traffic class may be redirected to the data node during the period of time to be handled according to the first traffic class.