Abstract: Aspects of the subject disclosure may include, for example, instantiating a virtual smartphone in a cloud infrastructure, installing a smartphone application on the virtual smartphone, receiving input sensor data from a physical user device, providing the input sensor data to the smartphone application on the virtual smartphone, receiving output data from the smartphone application on the virtual smartphone, and providing the output data to the physical user device. Other embodiments are disclosed.

Abstract: Methods, systems, and apparatuses, among other things, as described herein may provide for hyperlocal edge cache. A method includes intercepting a request for a resource/entity associated with an application; determining that the request can be served from the cache, wherein the cache is connected with a base station and only serves devices directly connected with the base station; and responding to fulfill the request for the resource associated with the application.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: In one example, a processing system may support capacity management in a virtualization environment based on hierarchical capacity management. The processing system may maintain a policy for a first capacity agent at a first hierarchical layer. The policy may include a set of key capacity indicators, a capacity limit, and an algorithm. The processing system may obtain, based on the set of key capacity indicators, a set of key capacity indicator information. The processing system may monitor, based on the capacity limit, for a detection of a capacity limit event. The processing system may determine, based on the algorithm, a predicted capacity exhaustion point. The processing system may send, toward a second capacity agent at a second hierarchical layer that is above the first hierarchical layer, the set of key capacity indicator information and the predicted capacity exhaustion point.

Abstract: Methods and systems for providing content. A selection of a single virtual channel may be received from the user. Virtual programming data for the single virtual channel may be accessed. The virtual programming data may define content to be provided over the single virtual channel. The content may be provided over the single virtual channel in accordance with the virtual programming data.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: A cloud oversubscription system including one or more processors and a memory coupled with the one or more processors. The one or more processors effectuate operations including obtaining a list of service level agreement (SLA) availability values for each of one or more virtual machines (VMs) of a host. The one or more processors further effectuate operations including analyzing the list to determine a maximum availability number for the host. The one or more processors further effectuate operations including identifying a probable overload condition value based on the SLA availability values. The one or more processors further effectuate operations including performing at least one recommended action when the probable overload condition value exceeds an SLA before an occurrence of an overload condition.

Abstract: A system for performing assurance of at least one network element in a network, the system comprising: at least one pacemaker, wherein the at least one pacemaker is a virtual machine in communication with a path to the at least one network element in the network, the at least one pacemaker configured to selectively provide an atomic workload to the path; a configuration analysis microservice in communication with the at least one pacemaker, the configuration analysis microservice is configured to provide a policy to the at least one pacemaker for application of the atomic workload and monitor a pulse from the atomic workload on the path.

Abstract: A method includes receiving, by a server, a data transmission of video content destined for a data storage device. The method includes generating, by the server, a content signature by application of a wavelet transform to a plurality of frames of a time sequence of frames of the video content. The method includes selecting, by the server based on content metadata for the video content, particular prohibited content signatures from a plurality of prohibited content signatures. Each prohibited content signature of the particular prohibited content signatures corresponds to a wavelet transform of a plurality of frames of prohibited content. The method also includes, in response to a first determination that a first prohibited content signature of the particular prohibited content signatures matches the content signature, preventing transmission of the video content from the server to the data storage device.

Abstract: A system for performing assurance of at least one network element in a network, the system comprising: at least one pacemaker, wherein the at least one pacemaker is a virtual machine in communication with a path to the at least one network element in the network, the at least one pacemaker configured to selectively provide an atomic workload to the path; a configuration analysis microservice in communication with the at least one pacemaker, the configuration analysis microservice is configured to provide a policy to the at least one pacemaker for application of the atomic workload and monitor a pulse from the atomic workload on the path.

Abstract: Methods and systems for providing content. A selection of a single virtual channel may be received from the user. Virtual programming data for the single virtual channel may be accessed. The virtual programming data may define content to be provided over the single virtual channel. The content may be provided over the single virtual channel in accordance with the virtual programming data.

Abstract: In one example, a processing system may support capacity management in a virtualization environment based on hierarchical capacity management. The processing system may maintain a policy for a first capacity agent at a first hierarchical layer. The policy may include a set of key capacity indicators, a capacity limit, and an algorithm. The processing system may obtain, based on the set of key capacity indicators, a set of key capacity indicator information. The processing system may monitor, based on the capacity limit, for a detection of a capacity limit event. The processing system may determine, based on the algorithm, a predicted capacity exhaustion point. The processing system may send, toward a second capacity agent at a second hierarchical layer that is above the first hierarchical layer, the set of key capacity indicator information and the predicted capacity exhaustion point.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, a dispatch system having a controller element to receive from a communication device a first wireless message including a location coordinate and a request for taxicab service, and determine available taxicab services according to the location coordinate and the request. Additional embodiments are disclosed.

Abstract: Methods and systems for providing content. A selection of a single virtual channel may be received from the user. Virtual programming data for the single virtual channel may be accessed. The virtual programming data may define content to be provided over the single virtual channel. The content may be provided over the single virtual channel in accordance with the virtual programming data.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: A cloud oversubscription system including one or more processors and a memory coupled with the one or more processors. The one or more processors effectuate operations including obtaining a list of service level agreement (SLA) availability values for each of one or more virtual machines (VMs) of a host. The one or more processors further effectuate operations including analyzing the list to determine a maximum availability number for the host. The one or more processors further effectuate operations including identifying a probable overload condition value based on the SLA availability values. The one or more processors further effectuate operations including performing at least one recommended action when the probable overload condition value exceeds an SLA before an occurrence of an overload condition.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: A cloud oversubscription system comprising an overload detector configured to model a time series of data of at least one virtual machine on a host as a vector-valued stochastic process including at least one model parameter, the overload detector communicating with an inventory database, the overload detector configured to obtain an availability requirement for each of the at least one virtual machine; a model parameter estimator communicating with the overload detector, the model parameter estimator communicating with a database containing resource measurement data for at least one virtual machine on a host at a selected time interval, the model parameter estimator is configured to estimate the at least one model parameter from the resource measurement data; a loading assessment module communicating with the model parameter module to obtain the at least one model parameter for each of the at least one host running at least one virtual machine and determine a probability of overload based on the at least one

Abstract: A method includes receiving a media request for a target device. The signaling information may be received from the target device and a media server. At least one attribute of the target device and the media server may be identified using the signaling information. At least one attribute of the target device and the media server may be evaluated against a service level objective to select a media format. The service level objective may include consideration of the target device and available bandwidth over a provider network. The media may be provided in the selected media format over the provider network to the target device.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.