Nokia Solutions and Networks Oy

Bilgehan Erman

Sameerkumar V Sharma

Bruce Cilli

Ejder Bastug

Andrea Francini

Raymond Miller

Edward Grinshpun

Charles Payette

Ahmad Asghar

Peter Andrews

Mahmoud Ashour

Luoyao Hao

Aspects described herein relate to various methods, systems and apparatuses that can be used to define a network slice based on descriptions of the computing functions involved in a network service, and to configure the network slice using resources that are associated with the descriptions. For example, a network slice may be defined based on whether the network service requires tunneling or data encryption. The network slice may be configured using resources that perform those tunneling and data encryption functions.

Configuring network slices

Various example embodiments for supporting congestion control in a communication network are presented. Various example embodiments for supporting congestion control in a communication network may be configured to support protocol agnostic cognitive congestion control in the communication network. Various example embodiments for supporting protocol agnostic cognitive congestion control in a communication network may be configured to support protocol agnostic cognitive congestion control in the communication network by enabling a sending node of a path over which a set of flows is to be communicated to determine the minimum target transmission rate among the links along the path over which the flows are to be communicated and to use the minimum target transmission rate among the links along the path over which flows are to be communicated in order to control transmission of packets over the path at Layer 3 of the Open Systems Interconnection (OSI) model.

Protocol agnostic cognitive congestion control

Various example embodiments for supporting multi-tier deterministic networking are presented. Various example embodiments for supporting multi-tier deterministic networking may be configured to support provisioning of deterministic flows in multi-tier deterministic networking. Various example embodiments for supporting multi-tier deterministic networking may be configured to support adaptive deterministic routing in multi-tier deterministic networks. Various example embodiments for supporting multi-tier deterministic networking may be configured to support score-based deterministic routing in multi-tier deterministic networks. Various example embodiments for supporting multi-tier deterministic networking may be configured to support adaptive deterministic routing and/or score-based deterministic routing in multi-tier deterministic networks based on analysis of a state representation for path and/or sub-path selection in multi-tier deterministic networks. Various example embodiments for supporting multi-tier deterministic networking may be configured to support hierarchical resource allocation and deallocation in multi-tier deterministic networking, optimal route finding in multi-tier deterministic networking, and so forth.

Multi-tier deterministic networking

An application specific interface (AA-NAPI) associated with an application for the purpose of controlling the networking aspects of the application session is provided by communication service provider (CSP). Cost model of network service types associated with a specific application type is learned by using the AA-NAPI. For each service-point joining the session, network properties are queried by using the AA-NAPI. During continuous service quality monitoring, upon detection of quality degradation leading to the decision to upgrade session quality, network service-type associated with a specific server-point is changed by using the AA-NAPI. Network specific actions are taken to reconfigure the network so that the requested service type is received by the specific service-point. New network capability is activated to improve network service level by using the AA-NAPI. Network specific actions are taken by the network to install new network capabilities so that the specific service-point's service quality is improved as requested.

Method, an apparatus and a computer program product for network-as-a-service model

A network node configured to transmit packets to a destination node in a packet network, includes at least one processor and at least one memory including computer program code. The at least one memory and the computer program code are configured to, with the at least one processor, cause the network node to: assemble at least a first packet including a plurality of data units, each of the plurality of data units being grouped into one of a connection group, a network function group or an application group; and transmit the first packet to the destination node.

Universal network protocol encapsulation and methods for transmitting data

Various example embodiments for supporting dynamic node cluster discovery in a communication network are presented. Various example embodiments for supporting dynamic node cluster discovery in a communication network may be configured to support dynamic node cluster discovery based on circulation of discovery messages within the communication network. Various example embodiments for supporting dynamic node cluster discovery based on the circulation of discovery messages within the communication network may be configured to support dynamic node cluster discovery based on probabilistic forwarding of discovery messages within the communication network. Various example embodiments for supporting dynamic node cluster discovery based on the circulation of discovery messages within the communication network may be configured to support dynamic node cluster discovery based on updating and forwarding of discovery messages within the communication network. Various example embodiments for supporting dynamic node cluster discovery in a communication network may be configured to support dynamic, multi-level node cluster discovery.

Dynamic node cluster discovery in an unknown topology graph

Various example embodiments for supporting flow reliability in deterministic networking are presented. Various example embodiments for supporting flow reliability in deterministic networking may be configured to support flow reliability in deterministic networking based on control over frame replication and elimination for deterministic flows. Various example embodiments for supporting flow reliability in deterministic networking based on control over frame replication and elimination for deterministic flows may be configured to control replication and elimination of redundant flows providing redundancy for deterministic flows based on dynamic activation and deactivation of the redundant flows based on monitoring of flow continuity of the deterministic flows. Various example embodiments for supporting flow reliability in deterministic networking based on control over frame replication and elimination for deterministic flows may be configured to support flow reliability in deterministic networking for non-hierarchical networks or hierarchical networks.

Flow reliability in multi-tier deterministic networking

A method for routing traffic between a source node and a destination node in a network comprises: identifying a first group level at which a source group vector and a destination group vector differ; obtaining one or more first route segments between a first source group and a first destination group at the first group level; computing an end-to-end route between the source node and the destination node based on at least the one or more first route segments; and routing traffic between the source node and the destination node on the end-to-end route.

Cluster oriented dynamic routing

A system and a method for interpreting normal and errored segments of network measurement data differently, and processing network measurement data, including: receiving a first query for network measurement data; extracting compressed network measurement data and error metadata from a repository database based upon the first query; decompressing the extracted compressed network measurement data; retrieving an error segment of raw network measurement data based upon the error metadata; and merging the error segment of raw network measurement data with the decompressed extracted compressed network measurement data to produce extracted network measurement data.

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Weehawken, NJ, United States of America

Bilgehan Erman