Abstract: A system described herein may provide a technique for generating one or more predictive models of device availability, which may be used to predict whether a given device will be able to be reached via one or more networks to receive information, such as Over-the-Air (“OTA”) updates. The predictive models may be based on, for example, radio frequency (“RF”) metrics, device availability metrics, and timing offsets between times associated with such RF metrics and availability metrics. For a given device, based on RF metrics associated with the device and further based on a candidate time, the predictive model may be used to determine whether the device will be available at the candidate time.

Abstract: A system described herein may provide a technique for generating one or more predictive models of device availability, which may be used to predict whether a given device will be able to be reached via one or more networks to receive information, such as Over-the-Air (“OTA”) updates. The predictive models may be based on, for example, radio frequency (“RF”) metrics, device availability metrics, and timing offsets between times associated with such RF metrics and availability metrics. For a given device, based on RF metrics associated with the device and further based on a candidate time, the predictive model may be used to determine whether the device will be available at the candidate time.

Abstract: A system described herein may provide a technique for generating one or more predictive models of device availability, which may be used to predict whether a given device will be able to be reached via one or more networks to receive information, such as Over-the-Air (“OTA”) updates. The predictive models may be based on, for example, radio frequency (“RF”) metrics, device availability metrics, and timing offsets between times associated with such RF metrics and availability metrics. For a given device, based on RF metrics associated with the device and further based on a candidate time, the predictive model may be used to determine whether the device will be available at the candidate time.

Abstract: In one embodiment, a method of energy-aware routing includes modifying a reference topology of a network by removing at least a portion of a first node from the reference topology, wherein the first node is associated with a power efficiency criterion. The method also includes determining whether one or more performance criteria are satisfied based on assessing a projected response of the modified reference topology to reference traffic. The method further includes scheduling at least partial shut-down of the first node in response to determining that the one or more performance criteria are satisfied. In some implementations, the one or more performance criteria include at least one of a latency threshold, a bandwidth utilization threshold, a redundancy criterion, and a power consumption threshold. In some implementations, the first node is one of a router, a line card, an interface, or a bundle of one or more ports.

Abstract: A system and method for automated monitoring of availability in xDSL access networks are disclosed. An xDSL access network with network availability monitoring generally comprises a measurement device in communication with a DSL access multiplexer (DSLAM) at a central office (CO), a broadband remote access server (BRAS) in communication with the DSLAM, a remote authentication dial-in user service (RADIUS) server in communication with the BRAS, and a data collector at a network operations center (NOC) in communication with the RADIUS server and the measurement device, the data collector being configured to retrieve data from the RADIUS server, the measurement device being configured to automatically establish a PPP session with the BRAS and the RADIUS server being adapted to collect data relating to the PPP session. The measurement device is preferably connected to the DSLAM via an xDSL loop terminating at a DSLAM monitoring port. In addition, the PPP session is preferably authenticated.