Abstract: A method includes, generating a schedule for an asset tag, the schedule defining: a unicast trigger time for transmission of a unicast trigger to the asset tag; a transmit time succeeding receipt of the multicast trigger; and a wake window intersecting the transmit time and the receipt of the multiact trigger. The method also includes transmitting the schedule from a node network to the asset tag and configuring the asset tag based on the schedule. The method also includes, at the node network, broadcasting the unicast trigger and, at an asset tag: entering a wake mode; receiving the unicast trigger; transmitting a ranging signal; and entering the sleep mode. The method further includes, at the node network: deriving location of the asset tag based on instance of the ranging signal received by nodes in the node network.

Abstract: Top-of-rack (TOR) switches are connected to a network fabric of a data center. Each TOR switch corresponds to a rack of the data center, and is configured to provide access to the network fabric for computing devices mounted in the rack. In one method, a TOR switch is mounted in a rack. The TOR switch is connected to a network fabric of a data center. A lock is used to control physical access to the rack. A request to physically access the rack is received from a computing device (e.g., a badge implementing a security token, or a mobile device). The request includes authentication credentials. The computing device is then authenticated. In response to authenticating the computing device, the lock is configured to provide physical access to the rack.

Abstract: Systems and methods are described herein for novel uses and/or improvements to artificial intelligence applications in an environment with limited or no available data. In particular, systems and methods are described herein for providing network arrangement recommendations based on power consumption predictions for selected applications within network arrangements featuring devices with non-homogenous or unknown specifications.

Abstract: Systems and methods are described herein for novel uses and/or improvements to artificial intelligence applications in an environment with limited or no available data. In particular, systems and methods are described herein for providing power consumption predictions for selected applications within network arrangements featuring devices with non-homogenous or unknown specifications.