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.

The described technology is directed towards presenting a server overload condition that can result from a spike in client requests. Upon receiving an incoming client request for data at a server, a request buffer condition of a client request buffer (e.g., a counter) is evaluated to determine whether the client request corresponds to an anticipated overload state with respect to a request-handling capability of the server, e.g., whether the client request buffer is full. If so, an overload response (e.g., a retry response) is returned to the client indicating so that the client retries a corresponding client request after a time delay. If not in the anticipated overload state, the request is further processed, e.g., to provide a regular response containing the requested data, such as by adding a request information entry associated with the incoming client request to the client request buffer and updating the request buffer condition.

Systems and methods are provided for determining release weights for geographic locations and specific times for selected users, and optimizing the timing of message notifications for a mobile device based on those release weights. The release weights may be determined based 1) generalized factors, 2) factors individualized for a particular mobile device user, and/or 3) real-time factors. These release weights are calculated to represent a user's likeliness to launch a client application from a message notification at a given time and geographic location.

Systems and methods are provided for determining release weights for geographic locations and specific times for selected users, and optimizing the timing of message notifications for a mobile device based on those release weights. The release weights may be determined based 1) generalized factors, 2) factors individualized for a particular mobile device user, and/or 3) real-time factors. These release weights are calculated to represent a user's likeliness to launch a client application from a message notification at a given time and geographic location.

A system and method for hybrid callback management with transparent user authentication, utilizing a callback cloud and an on-premise callback system, allowing users to be verified via his or her biometrics, and also allowing brands to utilize a hybrid system that protects against any premise outages or cloud service faults and failures by introducing redundancies and co-maintenance of data key to callback execution.

A method for determining location of a premises is disclosed. The method includes measuring a signal strength of a plurality of communication signals received at the premises, obtaining data associated with a source of the signals, estimating a propagation loss for the received signal, determining a distance between a source of each of the signals and the premises based on the estimated propagation loss, and triangulating the location of the premises.

Methods, systems, apparatuses, and computer program products are provided for prefetching data. A workload analyzer may identify job characteristics for a plurality of previously executed jobs in a workload executing on a cluster of one or more compute resources. For each job, identified job characteristics may include identification of an input dataset and an input bandwidth characteristic for the input dataset. A future workload predictor may identify future jobs expected to execute on the cluster based at least on the identified job characteristics. A cache assignment determiner may determine a cache assignment that identifies a prefetch dataset for at least one of the future jobs. A network bandwidth allocator may determine a network bandwidth assignment for the prefetch dataset. A plan instructor may instruct a compute resource of the cluster to load data to a cache local to the cluster according to the cache assignment and the network bandwidth assignment.

A control system determines whether a browser is retrieving supplemental content over a slow or faulty network using a tracking indicator. Based on determining that browser is retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser. The control system may modify responses by declining to bid, responding with a lower bid amount, or responding with alternate supplemental content. Based on determining that browser is no longer retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser by responding with a higher bid amount or responding with the original supplemental content. Thus, the control system maximizes the use of control system and campaign manager resources by responding to opportunities according to the likelihood that they will result in an impression or a conversion.

A control system determines whether a browser is retrieving supplemental content over a slow or faulty network using a tracking indicator. Based on determining that browser is retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser. The control system may modify responses by declining to bid, responding with a lower bid amount, or responding with alternate supplemental content. Based on determining that browser is no longer retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser by responding with a higher bid amount or responding with the original supplemental content. Thus, the control system maximizes the use of control system and campaign manager resources by responding to opportunities according to the likelihood that they will result in an impression or a conversion.

In one embodiment, a method includes receiving a user request from a first user at a client system, wherein the user request is associated with a semantic-intent, identifying dialog-intents associated with the user request by the client system based on the semantic-intent and context information associated with the user request, wherein each dialog-intent is a sub-intent of the semantic-intent; determining agents for executing tasks associated with the dialog-intents by the client system, and presenting information returned from the agents responsive to executing the tasks at the client system.