A forwarding entry generation method includes sending, by a controller, a plurality of resource allocation request messages to a plurality of network devices in a network slice, to trigger the plurality of network devices to allocate resources, where the resource allocation request message includes an identifier of the network slice and a resource that needs to be allocated by a corresponding network device to the network slice; receiving, by the controller, a plurality of resource allocation response messages including the identifier of the network slice and a segment identifier of a corresponding network device, and a resource allocated by each device belongs to the network slice; and generating, by the controller, a forwarding table corresponding to the network slice, where the forwarding table includes a forwarding entry for arriving at a network device in the network slice.

There is provided an apparatus comprising at least one processor and at least one memory including a computer program code. The at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to receive from at least one further apparatus information associated with at least two virtual network functions, compare the information associated with the at least two virtual network functions to a determined rule, generate at least one function control based on the comparing, and assign the at least one function control to at least one of the at least two virtual network functions.

A method comprising discovering workload attributes and identify dependencies, receiving utilization performance measurements including memory utilization measurements of at least a subset of workloads, grouping workloads based on the workload attributes, the dependencies, and the utilization performance measurements into affinity groups, determining at least one representative synthetic workload for each affinity group, each representative synthetic workload including a time slice of a predetermined period of time when there are maximum performance values for any number of utilization performance measurements among virtual machines of that particular affinity group, determining at least one cloud service provider (CSP)'s cloud services based on performance of the representative synthetic workloads, and generating a report for at least one of the representative synthetic workloads, the report identifying the at least one of the representative synthetic workloads and the at least one CSP's cloud services including cloud workload cost.

Systems and methods are provided for updating resource allocation in a distributed network. For example, the method may comprise allocating a plurality of resource containers in a distributed network in accordance with a first distributed resource configuration. Upon determining that a processing workload value exceeds a stabilization threshold of the distributed network, determining a resource efficiency value of the plurality of resource containers in the distributed network. When a resource efficiency value is greater than or equal to the threshold resource efficiency value, the method may generate a second distributed resource configuration that includes a resource upscaling process, or when the resource efficiency value is less than the threshold resource efficiency value, the method may generate the second distributed resource configuration that includes a resource outscaling process. The resource allocation may transmit the second to update the resource allocation.

This disclosure relates to decentralized computing networks, architectures and techniques for collecting, analyzing, and processing data over multiple channels. A decentralized computing network comprises a plurality of computing nodes, each of which is dedicated to analyzing and processing events for a particular channel corresponding to a geographic region. Each node of the decentralized computing network can operate independently to process channel analysis data for a corresponding channel. The decentralized configuration of the nodes enables efficient processing of data collected over large geographic areas, increases the reliability of the system, and facilitates easy scaling of the system. Other embodiments are disclosed herein as well.

This disclosure relates to decentralized computing networks, architectures and techniques for collecting, analyzing, and processing data over multiple channels. A decentralized computing network comprises a plurality of computing nodes, each of which is dedicated to analyzing and processing events for a particular channel corresponding to a geographic region. Each node of the decentralized computing network can operate independently to process channel analysis data for a corresponding channel. The decentralized configuration of the nodes enables efficient processing of data collected over large geographic areas, increases the reliability of the system, and facilitates easy scaling of the system. Other embodiments are disclosed herein as well.

There is provided a method for handling the running of software in a network, which is performed by a first node in response to a first request to run software using at least one infrastructure component and at least one function component. Transmission of a second request is initiated towards a second node. The second node manages the at least one infrastructure component. The second request is to deploy the at least one infrastructure component and comprises information indicative of at least one function-as-a-service (FaaS) platform implemented by the at least one infrastructure component to be used to run the software. Transmission of a third request is initiated towards a third node. The third node manages the at least one FaaS platform. The third request is to configure the at least one FaaS platform to run the software.

Aspects of the disclosure are directed to a software defined network (SDN) having a sharded control plane. The SDN may include a host device and a sharded control plane. The sharded control plane may include a first controller and a second controller sharded by one or more dimensions. The first controller and the second controller may be configured to process requests received from the first host device based on their respective sharded one or more dimensions. The one or more dimensions may be networks or functions.

For a communication network using a satellite-involved backhaul, the backhaul outage and restoration states are predicted based on satellite motion data. Based on such predictions, devices providing the core portion of the communication network, and nearby Internet or backhaul radio devices can schedule or take actions. Actions can include but are not necessarily limited to: powering equipment up or down, suspending communications, migrating software from servers being powered down, transmitting replies to packets to indicate an anticipated outage and optionally anticipated outage end time, marking packets with congestion indications, closing or reopening certain ports, withdrawing or reinstating routing table addresses, and transmitting outage notifications to users or devices.

This disclosure describes techniques that include provisioning compute nodes within a data center out of available pools of hardware. In one example, this disclosure describes a method that includes monitoring, by a computing system, a first workload executing on a first compute node, wherein the first compute node includes processing circuitry and first node secondary storage; monitoring, by the computing system, a second workload executing on a second cluster of compute nodes; expanding, by the computing system, the second cluster of compute nodes to include a second compute node that includes second node secondary storage; redeploying the processing circuitry included within the first compute node to the second compute node; and enabling, by the computing system, the second workload to continue executing on the second cluster of compute nodes including the second compute node.