A method for determining a designated forwarder (DF) of a multicast flow, a device, and a system are disclosed. In an Ethernet virtual private network (EVPN) scenario, a customer edge (CE) device is connected to a plurality of provider edge (PE) devices in a dual-homed or multi-homed manner. A first PE device is any one of the plurality of PE devices. After determining that the CE device connected to an Ethernet link joins a multicast group of a multicast flow, the first PE device determines bandwidth occupation statuses of a plurality of Ethernet links included in an Ethernet segment (ES) to which the Ethernet link belongs, and then determines, as a DF of the multicast flow based on the multicast flow bandwidth occupation statuses of the plurality of Ethernet links, a PE device corresponding to an Ethernet link that occupies lowest multicast flow bandwidth.

A method for determining a designated forwarder (DF) of a multicast flow, a device, and a system are disclosed. In an Ethernet virtual private network (EVPN) scenario, a customer edge (CE) device is connected to a plurality of provider edge (PE) devices in a dual-homed or multi-homed manner. A first PE device is any one of the plurality of PE devices. After determining that the CE device connected to an Ethernet link joins a multicast group of a multicast flow, the first PE device determines bandwidth occupation statuses of a plurality of Ethernet links included in an Ethernet segment (ES) to which the Ethernet link belongs, and then determines, as a DF of the multicast flow based on the multicast flow bandwidth occupation statuses of the plurality of Ethernet links, a PE device corresponding to an Ethernet link that occupies lowest multicast flow bandwidth.

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.

A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: identifying a plurality of asset resources within a data center; monitoring workloads within the data center, the monitoring providing data center workload data, the data center workload data including asset resource utilization data; determining whether certain asset resources are underutilized; presenting a load balance configurator user interface, the load balance configurator user interface enabling allocation of asset resources to target workloads; and, performing a data center asset allocation operation, the data center asset allocation operation reallocating workloads in response to the allocation of asset resources to target workloads.

An artificial intelligence enhanced method for optimizing operational deployment of field resources using network Voronoi Tessellations in combination with the aggregation and consideration of numerous data elements. Resources deployed in the field utilize modes of transportation that are represented by a network topology, which can be influenced by external sources of information that pertain to nodes in the network or nodes in other network topologies, which can be used by an artificial intelligence processor to develop optimized routes for deployed field resources in a continuous manner. The incorporation of these sources of information that can influence the topology of the network is utilized to determine the optimal deployment of field resources.

An artificial intelligence enhanced method for optimizing operational deployment of field resources using network Voronoi Tessellations in combination with the aggregation and consideration of numerous data elements. Resources deployed in the field utilize modes of transportation that are represented by a network topology, which can be influenced by external sources of information that pertain to nodes in the network or nodes in other network topologies, which can be used by an artificial intelligence processor to develop optimized routes for deployed field resources in a continuous manner. The incorporation of these sources of information that can influence the topology of the network is utilized to determine the optimal deployment of field resources.

The present disclosure relates to dynamically scheduling resource requests in a distributed system based on usage quotas. One example method includes identifying usage information for a distributed system including atoms, each atom representing a distinct item used by users of the distributed system; determining that a usage quota associated with the distributed system has been exceeded based on the usage information, the usage quota representing an upper limit for a particular type of usage of the distributed system; receiving a first request for a particular atom requiring invocation of the particular type of usage represented by the usage quota; determining that a second request for a different type of usage of the particular atom is waiting to be processed; and processing the second request for the particular atom before processing the first request.

The present disclosure relates to dynamically scheduling resource requests in a distributed system based on usage quotas. One example method includes identifying usage information for a distributed system including atoms, each atom representing a distinct item used by users of the distributed system; determining that a usage quota associated with the distributed system has been exceeded based on the usage information, the usage quota representing an upper limit for a particular type of usage of the distributed system; receiving a first request for a particular atom requiring invocation of the particular type of usage represented by the usage quota; determining that a second request for a different type of usage of the particular atom is waiting to be processed; and processing the second request for the particular atom before processing the first request.

A data processing program causes a processing device, among a plurality of processing devices each executes predetermined processing on received data and outputs a result, to execute a process. The process includes, calculating, in a case where a notification that a resource is increased is received from a first processing device in a group of processing devices at a previous stage of the processing device among the plurality of processing devices, a ratio of an amount of data received from the first processing device to a total amount of data received from each of the group of processing devices, based on an amount of data received from each of the group of processing devices within a predetermined period, and determining whether or not to increase a resource of the processing device based on the calculated ratio and resource usage of the processing device.

A data processing program causes a processing device, among a plurality of processing devices each executes predetermined processing on received data and outputs a result, to execute a process. The process includes, calculating, in a case where a notification that a resource is increased is received from a first processing device in a group of processing devices at a previous stage of the processing device among the plurality of processing devices, a ratio of an amount of data received from the first processing device to a total amount of data received from each of the group of processing devices, based on an amount of data received from each of the group of processing devices within a predetermined period, and determining whether or not to increase a resource of the processing device based on the calculated ratio and resource usage of the processing device.