# US 11,115,273 B2 · Analytics-driven dynamic network design and configuration > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,115,273 B2 - Document ID: US11115273B2 - Status: Granted - Kind: B2 - Application number: 16/573,856 - Filed: 2019-09-17 - Published: 2020-01-09 - Granted: 2021-09-07 - Earliest claimed: 2015-07-13 - Assignees: Telefonaktiebolaget LM Ericsson (publ) - Applicants: Telefonaktiebolaget Lm Ericsson (Publ) - Inventors: George Lapiotis; Chirag Parekh; Henry Chang; Kiran Patel - Web page: https://patentgrep.com/patent/US11115273B2 ## CPC - H04L 41/14: Network analysis or design - H04L 41/0803: Configuration setting - H04L 41/0816: the condition being an adaptation, e.g. in response to network events - H04L 41/142: using statistical or mathematical methods - H04L 41/16: using machine learning or artificial intelligence - H04L 43/062: related to network traffic - H04L 45/64: using an overlay routing layer - H04L 45/70: {Routing based on monitoring results} - H04L 67/51: Discovery or management thereof, e.g. service location protocol [SLP] or web services - H04L 67/535: {Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34)} - H04L 41/0895: Configuration of virtualised networks or elements, e.g. virtualised network function or OpenFlow elements - H04L 41/40: using virtualisation of network functions or resources, e.g. SDN or NFV entities - H04L 43/16: Threshold monitoring - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract A system and method for dynamically (re)configuring a service network based on profile information obtained from a Big Data Analytics platform. Received dynamic situation profiles relative to network states, subscriber states, etc. may be compared against corresponding characteristic situation profiles. If there is a similarity, a dynamic design change action may be effectuated for changing configuration of at least a part of the service network, e.g., a service chaining mechanism, operating to service user data flows of the subscribers. ## Claims ### Claim 1 A network configuration method, comprising: adaptively training a computer-implemented data analytics platform for generating situation profiles corresponding to a plurality of situations observed in a network serving a plurality of service users; obtaining a situation profile with respect to a particular situation, wherein the situation profile comprises values of one or more service user behavior events and one or more events pertaining to a state of the network servicing the plurality of service users; determining, in a matching operation, a similarity index between the situation profile and a characteristic situation profile applicable to the particular situation, wherein the characteristic situation profile comprises allowable values with respect to the service user behavior events and a plurality of network state events defining the particular situation; if the similarity index is within an acceptable window, generating one or more control signals to effectuate a design change action for changing configuration of at least a plurality of inline service nodes disposed in the network operating to service user data flows of the service users; and if the similarity index is not within the acceptable window, using the situation profile as a candidate actionable profile for generating one or more new characteristic situation profiles to be applied in subsequent matching operations against new situations. ### Claim 2 (depends on 1) The method as recited in claim 1, wherein the inline service nodes are configured in accordance with respective service chain policies corresponding to the plurality of service users, each service policy comprising an ordered sequence of inline services for traversal by a corresponding user data flow between an ingress and an egress node of the network. ### Claim 3 (depends on 2) The method as recited in claim 2, wherein the inline service nodes are operative to host a plurality of virtualized service functions and further wherein the design change action comprises at least one of instantiating a new virtualized service function, rearranging one or more existing virtualized service functions, generating one or more instances of an existing virtualized service function, cloning an existing service chain of one or more virtualized service functions, rerouting an existing service chain of one or more virtualized service functions, instantiating additional virtual machine resources, and removing one or more virtualized service functions. ### Claim 4 (depends on 1) The method as recited in claim 1, wherein one or more of the service user behavior events and the network state events are represented as variables comprising at least one of continuous variables, discrete variables, categorical variables, ordinal variables, real variables, Boolean variables, probabilistic variables and deterministic variables. ### Claim 5 (depends on 1) The method as recited in claim 1, wherein the situation profile and the characteristic situation profile each comprise a respective multidimensional vector. ### Claim 6 (depends on 1) The method as recited in claim 1, wherein the one or more new characteristic situation profiles are generated responsive to a supervisory evaluation received from at least one of a knowledge-based expert system and a human domain expert. ### Claim 7 (depends on 1) The method as recited in claim 1, wherein the network is configured as a Software-Defined Network (SDN) based on one of OpenFlow protocol and Forwarding and Control Element Separation (ForCES) protocol. ### Claim 8 (depends on 1) The method as recited in claim 1, wherein the similarity index between the situation profile and the characteristic situation profile is obtained as a vector distance comprising at least one of a Euclidean distance, a Hamming distance, a Chebychev distance, a Minkowsky distance, a Mahalanobis distance and a Bhattacharyya distance. ### Claim 9 (depends on 1) The method as recited in claim 1, wherein the similarity index between the situation profile and the characteristic situation profile is obtained based on a probabilistic dissimilarity between the two profiles' respective multidimensional data. ### Claim 10 (depends on 1) The method as recited in claim 1, further comprising: initializing a set of characteristic situation profiles corresponding to a number of predefined situations; and adaptively updating the set of characteristic situation profiles based on supervisory evaluation of situation profiles dynamically obtained with respect to the network. ### Claim 11 An apparatus, comprising: one or more processors; and one or more persistent memory modules having program instructions thereon, which perform following actions when executed by the one or more processors: adaptively training a computer-implemented data analytics platform for generating situation profiles with respect to a plurality of situations observed in a network serving a plurality of service users; processing a situation profile received in response to a particular situation, wherein the situation profile comprises values of one or more service user behavior events and one or more events pertaining to a state of the network servicing the plurality of service users; determining, in a matching operation, a similarity index between the situation profile and a characteristic situation profile applicable to the particular situation, wherein the characteristic situation profile comprises allowable values with respect to the service user behavior events and a plurality of network state events defining the particular situation; if the similarity index is within an acceptable window, generating one or more control signals to effectuate a design change action for changing configuration of at least a plurality of inline service nodes disposed in the network operating to service user data flows of the service users; and if the similarity index is not within the acceptable window, using the situation profile as a candidate actionable profile for generating one or more new characteristic situation profiles to be applied in subsequent matching operations against new situations. ### Claim 12 (depends on 11) The apparatus as recited in claim 11, wherein the inline service nodes are configurable in accordance with respective service chain policies corresponding to the plurality of service users, each service policy comprising an ordered sequence of inline services for traversal by a corresponding user data flow between an ingress and an egress node of the network. ### Claim 13 (depends on 12) The apparatus as recited in claim 12, wherein the inline service nodes are operative to host a plurality of virtualized service functions and further wherein the design change action comprises at least one of instantiating a new virtualized service function, rearranging one or more existing virtualized service functions, generating one or more instances of an existing virtualized service function, cloning an existing service chain of one or more virtualized service functions, rerouting an existing service chain of one or more virtualized service functions, instantiating additional virtual machine resources, and removing one or more virtualized service functions. ### Claim 14 (depends on 11) The apparatus as recited in claim 11, wherein one or more of the service user behavior events and the network state events are represented as variables comprising at least one of continuous variables, discrete variables, categorical variables, ordinal variables, real variables, Boolean variables, probabilistic variables and deterministic variables. ### Claim 15 (depends on 11) The apparatus as recited in claim 11, wherein the situation profile and the characteristic situation profile each comprise a respective multidimensional vector. ### Claim 16 (depends on 11) The apparatus as recited in claim 11, wherein the one or more new characteristic situation profiles are generated responsive to a supervisory evaluation received from at least one of a knowledge-based expert system and a human domain expert. ### Claim 17 (depends on 11) The apparatus as recited in claim 11, wherein the network is configured as a Software-Defined Network (SDN) based on one of OpenFlow protocol and Forwarding and Control Element Separation (ForCES) protocol. ### Claim 18 (depends on 11) The apparatus as recited in claim 11, wherein the similarity index between the situation profile and the characteristic situation profile is obtained as a vector distance comprising at least one of a Euclidean distance, a Hamming distance, a Chebychev distance, a Minkowsky distance, a Mahalanobis distance and a Bhattacharyya distance. ### Claim 19 (depends on 11) The apparatus as recited in claim 11, wherein the similarity index between the situation profile and the characteristic situation profile is obtained based on a probabilistic dissimilarity between the two profiles' respective multidimensional data. ### Claim 20 (depends on 11) The apparatus as recited in claim 11, wherein the program instructions further comprise instructions configured to: initialize a set of characteristic situation profiles corresponding to a number of predefined situations; and adaptively update the set of characteristic situation profiles based on supervisory evaluation of situation profiles dynamically obtained with respect to the network.