Abstract: A method for policing APN-AMBR includes, at P-GW including plural P-GW DP worker instances: receiving, uplink data to be transmitted over a non-GBR bearer associated with a first PDN session from a first UE via an AP or downlink data to be transmitted over the non-GBR bearer to the first UE via the AP; forwarding the uplink or downlink data to a first P-GW DP worker instance of the plurality of P-GW DP worker instances that is assigned to the PDN session; and, at the first P-GW DP worker instance, transmitting, to an APN-AMBR policer separate from the P-GW, a request for a slice of APN-AMBR capacity for processing the uplink or downlink data. The method further includes, at the APN-AMBR policer: maintaining records of APN-AMBR capacity used by UEs having PDN sessions assigned to different ones of the P-GW DP worker instances; and granting or denying the request based on the APN-AMBR capacity used by the PDN sessions assigned to the different ones of the P-GW DP worker instances.

Abstract: The present invention pertains to an Internet of things platform which includes: a middleware that includes an apparatus management unit for receiving apparatus generated information from an Internet of things apparatus so as to establish a connection to the Internet of things apparatus, a service management unit for abstracting the Internet of things apparatus into a service apparatus and for controlling the Internet of things apparatus according to a service scenario, and a data management unit for generating and storing data regarding the apparatus management unit, the service management unit and the Internet of things apparatus; and a script editor that generates the service scenario for the service apparatus.

Abstract: There are provided systems and methods for determining processing weights of rule variables for rule processing optimization. A service provider, such as an electronic transaction processor for digital transactions, may utilize different decision services that implement rules for decision-making of data including real-time data in production computing environments. Rules may correspond to coded statements that perform an automated decision-making service for the computing services and platforms of the service provider. When writing rules, different variables for data objects may be utilized, where each variable may perform a different operation and/or utilize a different operation for fetching and retrieving data used during rule processing. Each variable may therefore have a different data processing weights based on processing requirements of the data. Thus, optimization of rule authoring may be performed by mapping variables to other similar variables and showing a processing weight of each variable.

Abstract: An example embodiment may involve receiving, by a web server device and from a client device, a request for web content. The example embodiment may also involve determining, by the web server device, that a web document includes a script containing a synchronous client-side function call matching pre-determined criteria. The web content may be at least in part derivable from the web document. The example embodiment may also involve executing, by the web server device, the synchronous client-side function call to obtain output data. The example embodiment may also involve modifying, by the web server device, the web document to include the output data in a data structure associated with the synchronous client-side function call. The example embodiment may also involve transmitting, by the web server device and to the client device, the web document as modified.

Abstract: A resource distribution method, when different peer nodes communicate with each other, a key pair is used for encryption. A resource is transmitted in a ciphertext form in a peer-to-peer (P2P) network. In particular, each resource may have a corresponding key pair, and different key pairs may be used to encrypt resources of different users.

Abstract: Described are systems and methods for establishing and generating collections of sets that contain object identifiers based on user provided annotations for the object identifiers. A set may include one or more object identifiers and each object identifier may include one or more user provided annotations. Annotations from all object identifiers within a set are processed to form a set profile signature representative of the set. The set profile signatures are then compared between different sets to identify similar sets. Similar sets are included in a collection. Utilizing set profile signatures for a set formed based on user provided annotations provides useful relationships between sets that might otherwise not exist.

Abstract: In one example, a Network Functions Virtualization Orchestrator (NFVO) obtains a radio service descriptor defining communication parameters for a radio in a virtual Radio Access Network (vRAN). Based on the radio service descriptor, the NFVO determines whether a virtual Distributed Unit (vDU) that is configured in accordance with the communication parameters and a virtual Centralized Unit (vCU) that is configured in accordance with the communication parameters are already instantiated in the vRAN. If it is determined that the vDU or the vCU is not already instantiated, the NFVO automatically instantiates the vDU or the vCU in the vRAN.

Abstract: Operational metrics of a distributed collection of servers in a cloud environment are analyzed by a service to intelligently machine learn which operational metric is highly correlated to incidents or failures in the cloud environment. To do so, metric values of the operational metrics are analyzed over time by the service to check whether the operation metrics exceed a particular metric threshold. If so, the service also checks whether such spikes in the operation metric above the metric thresholds occurred during known cloud incidents. Statistics are calculated reflecting the number of times the operational metrics spiked during times of cloud incidents and spiked during times without cloud incidents. Correlation scores based on these statistics are calculated and used to select the correlated operational metrics that are most correlated to cloud failures.

Abstract: One exemplary system can determine a digital footprint for a user. The system can determine a first transmission pattern in which first content was transmitted to a first user device based at least in part on the digital footprint. The system can determine training data that includes a relationship between (i) one or more characteristics of the first content and (ii) the first transmission pattern. The system can then train a machine-learning-model using the training data to enable the machine-learning-model to predict a second transmission pattern in which to transmit second content that is different from the first content. The system can provide the second content as input to the machine-learning-model to obtain the second transmission pattern as output from the machine-learning-model. The system can cause the second content to be transmitted to the first user device in accordance with the second transmission pattern, which may conserve computing resources.

Abstract: A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose “seed” particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count.

Abstract: Some embodiments of the invention provide a novel architecture for providing context-aware middlebox services at the edge of a physical datacenter. In some embodiments, the middlebox service engines run in an edge host (e.g., an NSX Edge) that provides routing services and connectivity to external networks (e.g., networks external to an NSX-T deployment). Some embodiments use a novel architecture for capturing contextual attributes on host computers that execute one or more machines and providing the captured contextual attributes to context-aware middlebox service engines providing the context-aware middlebox services. In some embodiments, a context header insertion processor uses contextual attributes to generate a header including data regarding the contextual attributes (a “context header”) that is used to encapsulate a data message that is processed by the SFE and sent to the context-aware middlebox service engine.

Abstract: In the present disclosure, artificial intelligence (AI) processing is trained and leveraged to learn user-specific insights that are contextually relevant to a state of a user communication. Contextual information about a state of a user communication may be collected and analyzed. That contextual information may be cross-referenced with an extensive knowledge graph that is constructed from user context data. Exemplary AI processing may further be trained to apply a relevance analysis to assist with processing described herein including generation and curation of data insights that are most relevant to a state of a user communication. In some examples, the data insight generation process may be augmented by pre-generating data insights that may be relevant to a user communication prior to occurrence of the user communication. Further technical examples pertain to the rendering and presentation of representations of data insights through a graphical user interface (GUI).

Abstract: According to examples, an apparatus may include a memory on which is stored instructions that when executed by a processor, cause the processor to extract, from network traffic data, a connectivity matrix that identifies connectivity data between entities and group the entities into a plurality of clusters based on the extracted connectivity matrix. The processor may also, for each cluster of the plurality of clusters, identify at least one representative entity that is to represent the entities in the cluster and output the identified at least one representative entity for identification of group behaviors of the entities in the plurality of clusters, in which the identified group behaviors are to be used for information technology management.

Abstract: Disclosed is a computer network including a group of a plurality of computing resource infrastructures associated with a plurality of orchestrators responsible for allocating the resources of this infrastructure to one or more client applications and grouped into a swarm in which they are interconnected by a cooperation interface, the allocation of resources being decided by a decision method based firstly on evaluations distributed among the orchestrators, then on a consensus protocol between the orchestrators which is based on the evaluations and is carried out at the cooperation interface in order to choose one of the infrastructures of the group to host some or all of the client application.

Abstract: Aspects of the present invention disclose a method, computer program product, and system for generating messages in a real-time chat discourse. The method includes one or more processors identifying user profile data associated with a user engaged in a real-time chat discourse with a chatbot. The method further includes one or more processors analyzing the real-time chat discourse between the user and the chatbot. The method further includes one or more processors determining a baseline emotive level for the real-time chat discourse based on the user profile data and the analysis of the real-time chat discourse. The method further includes one or more processors determining real-time emotion information of messages of the user in the real-time chat discourse. The method further includes one or more processors determining whether the real-time emotion information deviates from the determined baseline emotive level.

Abstract: Methods, systems, and computer readable media for Diameter-peer-wide egress rate limiting include a process performed at a Diameter relay agent (DRA) and at a rate limiting policer. The process includes receiving service requests from Diameter-based consumers and forwarding the service requests to DRA worker instances. The process further includes, at the DRA worker instances, requesting, from the rate limiting policer, which is separate from the DRA worker instances, Diameter peer capacity for handling the service requests. The process includes, at the rate limiting policer, performing Diameter-peer-wide egress rate limiting between the DRA worker instances and Diameter peer instances by granting or denying requests for Diameter peer capacity from the DRA worker instances such that combined egress traffic from the DRA worker instances does not exceed rate capacities of the Diameter peers.

Abstract: The present disclosure makes it possible to properly arrange mobile shop vehicles. An apparatus for determining arrangement of mobile shop vehicles comprises a controller configured to set a user of a shop group formed by the plurality of mobile shop vehicles; and determine the arrangement of the plurality of mobile shop vehicles on the basis of information that represents at least one of an attribute, a taste, and a purchase history of the user.

Abstract: In one embodiment, a method includes receiving current session information associated with a first user from a beacon associated with a third-party content provider, wherein the current session information indicates that a first client system of the first user is in an active wireless communication session with the beacon, accessing session information associated with one or more second users, wherein each second user is within a threshold geographical distance of the beacon, selecting one or more of the one or more second users based on the accessed session information, wherein the accessed session information associated with each of the selected second users indicates that a second client system associated with the selected second user is not in a wireless communication session with the beacon, and sending a notification referencing the selected one or more second users to the first client system.

Abstract: A method for processing an incoming call to a called terminal in a telecommunications network, implemented by a TAS server in an IMS network. The method includes: interrogating an SDM entity to determine whether the service profile of the user associated with the called terminal contains IN terminating service information; interrogating an SDM entity to determine whether the routing domain to be used to route the call to the called terminal is a circuit or packet type; if the routing domain is a packet type, determining whether the called terminal is effectively reachable in packet mode, and if applicable, via which type of access network; if the service profile contains IN terminating information, allowing the IN terminating service provided for the user of the called terminal to be distinguished according to the type of access network of the called terminal; and routing the call to the called terminal.

Abstract: In one embodiment, a device in a network obtains data indicative of a device classification rule, a device type label associated with the rule, and a set of positive and negative feature vectors used to create the rule. The device replaces similar feature vectors in the set of positive and negative feature vectors with a single feature vector, to form a reduced set of feature vectors. The device applies differential privacy to the reduced set of feature vectors. The device sends a digest to a cloud service. The digest comprises the device classification rule, the device type label, and the reduced set of feature vectors to which differential privacy was applied. The service uses the digest to train a machine learning-based device classifier.