Abstract: Systems, methods, and apparatuses for remote evaluation of content delivery service are described. A remote computing device may determine the existence and performance characteristics of devices and equipment at a premises by monitoring and analyzing data from a network associated with the premises to determine the presence or absence of equipment, compatibility issues, and performance quality.

Abstract: Described herein is a system and method for determining one or more data modulation profiles for one or more devices. The system and method described herein may measure signal quality, such as a modulation error ratio (MER), signal-to-noise ratio (SNR), receive power, transmit power, etc. Based on the signal quality, the system may determine one or more data modulation profile(s) (e.g., quadrature amplitude modulation (QAM) profiles) for a subcarrier, a plurality of subcarriers, a device, and/or a grouping of devices.

Abstract: A network may provide latency optimization by configuring respective latency values of one or more network components. A latency manager may receive a request indicative of a maximum latency value of a communications path between two devices, and may determine a particular network latency value. The latency manager may then determine respective endpoint latency values for endpoint devices based on the maximum latency value and network latency values. In addition, buffer characteristics, such as buffer depth at particular devices, may be adjusted in view of the latencies.

Abstract: Systems, methods, and apparatuses for remote evaluation of content delivery service are described. A remote computing device may determine the existence and performance characteristics of devices and equipment at a premises by monitoring and analyzing data from a network associated with the premises to determine the presence or absence of equipment, compatibility issues, and performance quality.

Abstract: Systems, methods, and apparatuses for remote evaluation of content delivery service are described. A remote computing device may determine the existence and performance characteristics of devices and equipment at a premises by monitoring and analyzing data from a network associated with the premises to determine the presence or absence of equipment, compatibility issues, and performance quality.

Abstract: A network may provide latency optimization by configuring respective latency values of one or more network components. A latency manager may receive a request indicative of a maximum latency value of a communications path between two devices, and may determine a particular network latency value. The latency manager may then determine respective endpoint latency values for endpoint devices based on the maximum latency value and network latency values. In addition, buffer characteristics, such as buffer depth at particular devices, may be adjusted in view of the latencies.

Abstract: Systems, apparatuses, and methods are described for evaluating profiles used for communication with a user device. A computing device may receive a signal associated with a profile. The computing device may analyze the received signal, and may determine, based on the analysis of the received signal, a simulation configuration associated with the profile. A simulation associated with the profile may be performed. The computing device may request or cause, based on the simulation, a change of the profile.

Abstract: A network may provide latency optimization by configuring respective latency values of one or more network components. A latency manager may receive a request indicative of a maximum latency value of a communications path between two devices, and may determine a particular network latency value. The latency manager may then determine respective endpoint latency values for endpoint devices based on the maximum latency value and network latency values. In addition, buffer characteristics, such as buffer depth at particular devices, may be adjusted in view of the latencies.

Abstract: Systems, methods, and apparatuses for remote evaluation of content delivery service are described. A remote computing device may determine the existence and performance characteristics of devices and equipment at a premises by monitoring and analyzing data from a network associated with the premises to determine the presence or absence of equipment, compatibility issues, and performance quality.

Abstract: Systems, methods, and apparatuses for remote evaluation of content delivery service are described. A remote computing device may determine the existence and performance characteristics of devices and equipment at a premises by monitoring and analyzing data from a network associated with the premises to determine the presence or absence of equipment, compatibility issues, and performance quality.

Abstract: A network may provide latency optimization by configuring respective latency values of one or more network components. A latency manager may receive a request indicative of a maximum latency value of a communications path between two devices, and may determine a particular network latency value. The latency manager may then determine respective endpoint latency values for endpoint devices based on the maximum latency value and network latency values. In addition, buffer characteristics, such as buffer depth at particular devices, may be adjusted in view of the latencies.

Abstract: Systems, methods, and apparatuses for remote evaluation of content delivery service are described. A remote computing device may determine the existence and performance characteristics of devices and equipment at a premises by monitoring and analyzing data from a network associated with the premises to determine the presence or absence of equipment, compatibility issues, and performance quality.

Abstract: A network may provide latency optimization by configuring respective latency values of one or more network components. A latency manager may receive a request indicative of a maximum latency value of a communications path between two devices, and may determine a particular network latency value. The latency manager may then determine respective endpoint latency values for endpoint devices based on the maximum latency value and network latency values. In addition, buffer characteristics, such as buffer depth at particular devices, may be adjusted in view of the latencies.

Abstract: A network may provide latency optimization by configuring respective latency values of one or more network components. A latency manager may receive a request indicative of a maximum latency value of a communications path between two devices, and may determine a particular network latency value. The latency manager may then determine respective endpoint latency values for endpoint devices based on the maximum latency value and network latency values. In addition, buffer characteristics, such as buffer depth at particular devices, may be adjusted in view of the latencies.

Abstract: A network may provide latency optimization by configuring respective latency values of one or more network components. A latency manager may receive a request indicative of a maximum latency value of a communications path between two devices, and may determine a particular network latency value. The latency manager may then determine respective endpoint latency values for endpoint devices based on the maximum latency value and network latency values. In addition, buffer characteristics, such as buffer depth at particular devices, may be adjusted in view of the latencies.

Abstract: A network may provide latency optimization by configuring respective latency values of one or more network components. A latency manager may receive a request indicative of a maximum latency value of a communications path between two devices, and may determine a particular network latency value. The latency manager may then determine respective endpoint latency values for endpoint devices based on the maximum latency value and network latency values. In addition, buffer characteristics, such as buffer depth at particular devices, may be adjusted in view of the latencies.