A method for training an analytics engine hosted by an edge server device is provided. The method includes determining a classification for data in an analytics engine hosted by an edge server and computing a confidence level for the classification. The confidence level is compared to a threshold. The data is sent to a cloud server if the confidence level is less than the threshold. A reclassification is received from the cloud server and the analytics engine is trained based, at least in part, on the data and the reclassification.

Disclosed herein are a method for operating a relation server and a system using the method. The method for operating the relation server for managing relations between machines includes generating, by the relation server, a capability set required to execute a command by analyzing the command, and grouping, by the relation server, machines that are to execute the command, among the machines, based on the generated capability set, and capability parameters and status parameters of respective machines that have been previously registered in the relation server or that are extractable by the relation server.

Disclosed herein are a method for operating a relation server and a system using the method. The method for operating the relation server for managing relations between machines includes generating, by the relation server, a capability set required to execute a command by analyzing the command, and grouping, by the relation server, machines that are to execute the command, among the machines, based on the generated capability set, and capability parameters and status parameters of respective machines that have been previously registered in the relation server or that are extractable by the relation server.

Support of coexistence of wireless transmission equipment in shared wireless medium environments is disclosed, which is applicable to various types of wireless transmission equipment. For instance, a wireless power transmission system (WPTS) delivers power to wireless power receiver clients via transmission of wireless power signals using one or more frequencies and/or channels within shared wireless medium environments in which other wireless equipment is operating, such as access points and stations in wireless local area networks (WLANs). The WPTS is configured to co-exist with the operations of the other wireless equipment within the shared wireless medium environment by adapting its transmission operations to utilize frequencies or channels that do not interfere with other equipment and/or implementing co-channel and shared channels operations under which access to channels is implemented using standardized WLAN protocols such as PHY and MAC protocols used for 802.11 (Wi-Fi™) networks.

One example method includes receiving data segments that are not already part of a full disk image of a backup, storing the data segments in storage, determining whether or not an aggregate total of data segments in the storage, that are not already part of a full disk image of a backup, equals or exceeds a threshold, when the aggregate total of data segments in the storage equals or exceeds the threshold, creating a full disk image of a backup that includes the data segments in storage, and storing the created full disk image of the backup to a recovery disk.

A system includes processing circuitry; and a memory device including instructions embodied thereon, wherein the instructions, which when executed by the processing circuitry, configure the processing circuitry to perform operations comprising: accessing input data, at an aggregator node, the input data including sensor data from a plurality of sensor nodes, each sensor data having a respective signature; validating the sensor data by using respective cryptographic hash functions on the sensor data and evaluating the respective result using the respective signature; performing an aggregation function on the sensor data to produce aggregate data; executing a hash function on the aggregate data to produce a hash value for the aggregate data; bundling the sensor data, respective signatures of the sensor data, aggregate data, and hash value for the aggregate data in a data structure; and exposing the data structure to subscriber nodes on the IoT network.

A system includes processing circuitry; and a memory device including instructions embodied thereon, wherein the instructions, which when executed by the processing circuitry, configure the processing circuitry to perform operations comprising: accessing input data, at an aggregator node, the input data including sensor data from a plurality of sensor nodes, each sensor data having a respective signature; validating the sensor data by using respective cryptographic hash functions on the sensor data and evaluating the respective result using the respective signature; performing an aggregation function on the sensor data to produce aggregate data; executing a hash function on the aggregate data to produce a hash value for the aggregate data; bundling the sensor data, respective signatures of the sensor data, aggregate data, and hash value for the aggregate data in a data structure; and exposing the data structure to subscriber nodes on the IoT network.

A distributed computing system uses dynamically calculates a subset size for each of a plurality of load balancers. Each of a plurality of load balancers logs requests from client devices for connections to back-end servers and periodically sends a request report to a traffic aggregator, which aggregates the report requests from the load balancers in the corresponding zone. Each traffic aggregator sends the aggregated request data to a traffic controller, which aggregates the request data to determine a total number of requests received at the system. The total request data is transmitted through each traffic aggregator to each load balancer instance, which calculates a percentage of the total number of requests produced by the load balancer and determines a subset size based on the calculated percentage.

Techniques for preventing concurrent execution of an infrastructure orchestration service are described. Worker nodes can receive instructions, or tasks, for deploying infrastructure resources and can provide heartbeat notifications to scheduler nodes, also considered a lease. A signing proxy can track the heartbeat notifications sent from the worker nodes to the scheduler node. The signing proxy can receive requests corresponding to a performance of the tasks assigned to the worker nodes. The signing proxy can determine whether the lease between each worker node and the scheduler is valid. If the lease is valid, the signing proxy may make a call to services on behalf of the worker node, and if the lease is not valid, the signing proxy may not make a call to services on behalf of the worker node. Instead, the signing proxy may cut off all outgoing network traffic, blocking access of the worker node to services.

Techniques for preventing concurrent execution of an infrastructure orchestration service are described. Worker nodes can receive instructions, or tasks, for deploying infrastructure resources and can provide heartbeat notifications to scheduler nodes, also considered a lease. A signing proxy can track the heartbeat notifications sent from the worker nodes to the scheduler node. The signing proxy can receive requests corresponding to a performance of the tasks assigned to the worker nodes. The signing proxy can determine whether the lease between each worker node and the scheduler is valid. If the lease is valid, the signing proxy may make a call to services on behalf of the worker node, and if the lease is not valid, the signing proxy may not make a call to services on behalf of the worker node. Instead, the signing proxy may cut off all outgoing network traffic, blocking access of the worker node to services.