Patent classifications
H04L47/78
System for source independent but source value dependent transfer monitoring
Systems, computer program products, and methods are described herein for source independent but source value dependent transfer monitoring. The invention is configured to receive a processing request to initiate a processing network session, wherein the processing network session is associated with the processing of a first activity; receive, a processing interaction request to access a first resource associated with the user; extract a resource processing value associated with the first activity from the processing parameter data structure; determine whether the resource processing value is associated with triggering at least one block intervention step; block the entity input device from accessing the first resource in response to determining that the resource processing value is associated with triggering the at least one block intervention step during processing of the first activity; transmit a block notification to the entity input device; and trigger display of a success notification at an end-user application.
Load adaptation architecture framework for orchestrating and managing services in a cloud computing system
According to one aspect of the concepts and technologies disclosed herein, a cloud computing system can include a load adaptation architecture framework that performs operations for orchestrating and managing one or more services that may operate within at least one of layers 4 through 7 of the Open Systems Interconnection (“OSI”) communication model. The cloud computing system also can include a virtual resource layer. The virtual resource layer can include a virtual network function that provides, at least in part, a service. The cloud computing system also can include a hardware resource layer. The hardware resource layer can include a hardware resource that is controlled by a virtualization layer. The virtualization layer can cause the virtual network function to be instantiated on the hardware resource so that the virtual network function can be used to support the service.
Load adaptation architecture framework for orchestrating and managing services in a cloud computing system
According to one aspect of the concepts and technologies disclosed herein, a cloud computing system can include a load adaptation architecture framework that performs operations for orchestrating and managing one or more services that may operate within at least one of layers 4 through 7 of the Open Systems Interconnection (“OSI”) communication model. The cloud computing system also can include a virtual resource layer. The virtual resource layer can include a virtual network function that provides, at least in part, a service. The cloud computing system also can include a hardware resource layer. The hardware resource layer can include a hardware resource that is controlled by a virtualization layer. The virtualization layer can cause the virtual network function to be instantiated on the hardware resource so that the virtual network function can be used to support the service.
Method and Apparatus for Establishing Forwarding Path, and Computer-Readable Storage Medium
A method and an apparatus for establishing a forwarding path, the method including obtaining, by a first network node, path information of a to-be-established forwarding path, where the path information comprises an identifier of a network node on the forwarding path and a transmission resource requirement that needs to be allocated by the network node to the forwarding path, and sending a path establishment request packet based on the path information, where a packet header of the path establishment request packet comprises the path information, and where the path establishment request packet triggers the network node to allocate a transmission resource to the forwarding path based on the transmission resource requirement.
DYNAMIC ALLOCATION OF COMPUTING RESOURCES
The exemplary embodiments disclose a method, a computer program product, and a computer system for allocating computing resources. The exemplary embodiments may include collecting data of one or more users, wherein the collected data comprises calendar data of the one or more users, extracting one or more features from the collected data, and allocating one or more computing resources to one or more of the users based on the extracted one or more features and one or more models.
ENHANCED REDEPLOYING OF COMPUTING RESOURCES
Examples described herein relate to method, resource management system, and non-transitory machine-readable medium for redeploying a computing resource. Data related to a performance parameter corresponding to a plurality of computing resources deployed on a plurality of host-computing nodes may be received. The performance parameter is associated with one or both of: communication between computing resources of the plurality of computing resources, or communication of the plurality of computing resources with a network device. Further, for a computing resource of the plurality of computing resources, a candidate host-computing node is determined from the plurality of host-computing nodes based on the data related to the performance parameter and the computing resource may be redeployed on the candidate host-computing node.
System and method for supporting a usage calculation process in a cloud infrastructure environment
Systems and methods described herein support a usage calculation process in a cloud infrastructure environment. The usage calculation process can be used to determine whether a requested transaction that targets a compartment within a tree-structure of compartments violates any compartment quota or limit within parent compartments within the tree-structure.
DYNAMIC BANDWIDTH ALLOCATION IN CLOUD NETWORK SWITCHES BASED ON TRAFFIC DEMAND PREDICTION
Embodiments for dynamic bandwidth allocation in cloud network switches in a cloud computing environment are provided. Quality of service (QoS) policies may be dynamically changed in one or more cloud network switches based on dynamically estimating expected traffic demands for each of a plurality of traffic classes, wherein bandwidth is dynamically allocated among queues based on changing the QoS policies.
SYSTEMS AND METHODS FOR MULTI-CLOUD VIRTUALIZED INSTANCE DEPLOYMENT AND EXECUTION
A system may receive a first definition for a virtualized instance of a network function. The first definition may include a first set of declarations in a first format that is different than respective formats supported by different virtualized environments. The system may select a first virtualized environment to run the virtualized instance based on requirements specified within the first definition, and may generate a second definition with a second set of declarations that map the first set of declarations from the first format to a second format supported by the first virtualized environment. The system may deploy the virtualized instance to the first virtualized environment using the second set of declarations from the second definition. Deploying the virtualized instance may include configuring its operation based on some of the second set of declarations matching a configuration format supported by the first virtualized environment.
Enhanced selection of cloud architecture profiles
This document describes modeling and simulation techniques to select a cloud architecture profile based on correlations between application workloads and resource utilization. In some aspects, a method includes obtaining infrastructure data specifying utilization of computing resources of an existing computing system. Application workload data specifying tasks performed by one or more applications running on the existing computing system is obtained. One or more models are generated based on the infrastructure data and the application workload data. The model(s) define an impact on utilization of each computing resource in response to changes in workloads of the application(s). A workload is simulated, using the model(s), on a candidate cloud architecture profile that specifies a set of computing resources. A simulated utilization of each computing resource of the candidate cloud architecture profile is determined based on the simulation. An updated cloud architecture profile is generated based on the simulated utilization.