Systems and methods are described herein for streaming during unavailability of a content server. Upon determining that there are conditions indicating buffering issues during delivery of a media asset, a server determines a first group of devices suitable for receiving the media asset from the server and sharing the media asset on a peer-to-peer network. Then, the server determines a second group of devices suitable for receiving the media asset on a peer-to-peer network from a first group device. The server then determines groupings within which to share and receive the media asset. Next, the server transmits instructions to the devices in the first group to maintain in buffer and share certain portions of the media asset with the second group devices within their grouping. Finally, the server updates information detailing the media asset portions the devices are maintaining in buffer and sharing.

A method, computer system, and a computer program product for dynamic internet of things (IoT) device grouping is provided. After an initial location of an IoT device is set, a current location of the IoT device is later determined. Thereafter, the determined current location is compared to the initial location. Responsive to determining that the current location does not match the initial location based on the comparing, a new IoT device group is assigned to the IoT device.

A method, computer system, and a computer program product for dynamic internet of things (IoT) device grouping is provided. After an initial location of an IoT device is set, a current location of the IoT device is later determined. Thereafter, the determined current location is compared to the initial location. Responsive to determining that the current location does not match the initial location based on the comparing, a new IoT device group is assigned to the IoT device.

A server of a distributed computing system that is at least partially hosted on a particular access network receives a plurality of messages from a plurality of devices over a network, each of the messages associated with a corresponding source address. For each of the plurality of devices, a current access network is determined for the device. For each of the devices with a current access network being the particular access network, a first network policy is applied to the device. For each of the devices with a current access network being other than the particular access network, a second network policy is applied to the device, the second network policy defining a second encryption requirement.

A server of a distributed computing system that is at least partially hosted on a particular access network receives a plurality of messages from a plurality of devices over a network, each of the messages associated with a corresponding source address. For each of the plurality of devices, a current access network is determined for the device. For each of the devices with a current access network being the particular access network, a first network policy is applied to the device. For each of the devices with a current access network being other than the particular access network, a second network policy is applied to the device, the second network policy defining a second encryption requirement.

In one embodiment, a computer networking device calculates a first hash value for an identifier of a group of computing devices, as well as a second hash value for the identifier of the group of computing devices, with each hash value being at least in part on the identifier of the group of computing devices and an identifier of the respective interface. The computer networking device may also analyze the first hash value with respect to the second hash value and select the first interface for association with the identifier of the group of computing devices based at in part on the analyzing. The computer networking device may further store an indication that the identifier of the group of computing devices is associated with the first interface.

The present technology provides a system, method and computer-readable medium for configuration pattern recognition and inference, directed to a device with an existing configuration, through an extensible policy framework. The policy framework uses a mixture of python template logic and CLI micro-templates as a mask to infer the intent behind an existing device configuration in a bottom-up learning inference process. Unique values for device/network identifiers and addresses as well as other resources are extracted and accounted for. The consistency of devices within the fabric is checked based on the specific policies built into the extensible framework definition. Any inconsistencies found are flagged for user correction or automatically remedied by a network controller. This dynamic configuration pattern recognition ability allows a fabric to grow without being destroyed and re-created, thus new devices with existing configurations may be added and automatically configured to grow a Brownfield fabric.

The present technology provides a system, method and computer-readable medium for configuration pattern recognition and inference, directed to a device with an existing configuration, through an extensible policy framework. The policy framework uses a mixture of python template logic and CLI micro-templates as a mask to infer the intent behind an existing device configuration in a bottom-up learning inference process. Unique values for device/network identifiers and addresses as well as other resources are extracted and accounted for. The consistency of devices within the fabric is checked based on the specific policies built into the extensible framework definition. Any inconsistencies found are flagged for user correction or automatically remedied by a network controller. This dynamic configuration pattern recognition ability allows a fabric to grow without being destroyed and re-created, thus new devices with existing configurations may be added and automatically configured to grow a Brownfield fabric.

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.

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.