Abstract:
Techniques relating to a geographic lighting controller. A controller determines a target lighting pattern based on an instruction for a smart lighting effect. The controller retrieves from a database, based on the target geographic location, information identifying a first plurality of smart lights to activate as part of the smart lighting effect. The controller determines a plurality of network addresses for the first plurality of smart lights, based on the retrieved information, generates a lighting effect command relating to the first plurality of smart lights, and transmits the lighting effect command to create the smart lighting effect.
Abstract:
Techniques for accelerated Time series analysis (TSA) in a network are described. Packets from a first network flow at a network element, such as a switch or a router, are trapped using a hardware based TSA engine at the network element. The packets are then reduced into TSA tuples including TSA data points and stored into memory. A software based TSA module performs one or more TSA actions on the stored tuples, where the TSA actions produce analysis results used to determine network performance for the network and network based applications.
Abstract:
In one embodiment, a method comprises: establishing a first broadband data link between a first mobile narrowbeam transceiver positioned on a vehicle and a first fixed narrowbeam transceiver mounted along a prescribed path of the vehicle; and switching from the first broadband data link, by the first mobile narrowbeam transceiver, to a second broadband data link with a second fixed narrowbeam transceiver mounted along the prescribed path after the first fixed narrowbeam transceiver, enabling the vehicle to maintain continuous broadband access to a wide area network via a prescribed sequence of the fixed narrowbeam transceivers along the prescribed path.
Abstract:
In one embodiment, a battery backup unit (BBU) cut-off and recharge circuit includes: a first transistor, a power entry connection connected to a main power supply, where power from the power entry connection flows to application circuits for an electronic device, and the first transistor is positioned between a BBU and the power entry connection, and a microcontroller, where the microcontroller is operative to: detect a loss of power from the main power supply, turn on the first transistor to enable the BBU to discharge through the power entry connection to application circuits, detect a status of charge (SOC) for the BBU, and upon detecting that the SOC is under a predefined threshold, set the BBU cut-off and recharge circuit to a lockdown state by turning off the first transistor.
Abstract:
In one embodiment, a method comprises receiving, by an apparatus, a Media Access Control (MAC) frame destined for a destination device; dividing, by the apparatus, the MAC frame into frame fragments; coding the frame fragments into encoded cells; and causing, by the apparatus, transmission of selected subsets of the encoded cells, as distinct flows of the encoded cells, by respective optical physical layer transmitter devices reachable by the destination device.
Abstract:
A method is performed by a first fog node of a plurality of fog nodes. In some implementations, the first fog node includes a non-transitory memory and one or more processors coupled with the non-transitory memory. In some implementations, the method includes maintaining a distributed ledger in coordination with the remaining fog nodes of the plurality of fog nodes. In some implementations, the distributed ledger stores configuration information associated with one or more devices. In some implementations, the method includes obtaining a request for configuration information from a device that breaches a resource threshold associated with the distributed ledger. In some implementations, the method includes transmitting, to the device, the configuration information associated with the device in order to allow the device to be configured in accordance with the configuration information while the device breaches the resource threshold associated with the distributed ledger.
Abstract:
In one embodiment, a data processing device includes power port units for connection to network devices. Each power port unit is selectively configurable to operate as either (i) a Power Source Equipment port unit to provide power to a network device, or (ii) a Powered Device (PD) port unit to sink power from a network device. The device also includes a processor. In response to a power supply failure, the processor is operative to poll at least two network devices to determine if they are able to supply power, receive a response from each of the at least two network devices, and configure at least two power port units as PD port units to sink power from the at least two network devices. At least part of the received power is transferred from the at least two power port units via a power summing node to at least one local load.
Abstract:
In one embodiment, a battery backup unit (BBU) cut-off and recharge circuit includes: a first transistor, a power entry connection connected to a main power supply, where power from the power entry connection flows to application circuits for an electronic device, and the first transistor is positioned between a BBU and the power entry connection, and a microcontroller, where the microcontroller is operative to: detect a loss of power from the main power supply, turn on the first transistor to enable the BBU to discharge through the power entry connection to application circuits, detect a status of charge (SOC) for the BBU, and upon detecting that the SOC is under a predefined threshold, set the BBU cut-off and recharge circuit to a lockdown state by turning off the first transistor.
Abstract:
Techniques for orchestrating a machine learning (ML) system on a distributed network. Determined performance levels for a ML system, determined from performance data received from the distributed network, are compared to performance requirements from the ML system. An orchestration module for the ML system then determines adjustments for the ML system that will improve the performance of the ML system and executes the adjustments for the ML system.
Abstract:
Embodiments herein receive a request to reserve a fog computing resource for an end device, where the request includes a specified future time at which the fog computing resource will be used by the end device. It is determined that sufficient fog computing resources are available at the specified future time on a first fog node of a plurality of fog nodes. The fog computing resource of the first fog node is reserved for the specified future time, and an address corresponding to the first fog node is transmitted.