Abstract: The techniques described herein involve analysis of communication data included in trace file(s) of device(s) involved in a communication. These trace file(s) may each include data associated with multiple layers of a communication protocol stack of a respective device or data associated with a single such layer. The techniques may further involve one or more of determination of performance metrics associated with data at a specific layer of a specific device, correlation of the data between layers of a device, or correlation of data across multiple device(s) involved in the communication. The performance metrics or correlated data may then be analyzed based on thresholds or models to determine whether the performance metrics or correlated data exhibits a degraded quality of user experience. Also or instead, graphic or textual representations of the performance metrics or correlated data may be generated.

Abstract: The techniques described herein detect which one of multiple different radio states a radio communication unit of a client device is currently operating in. The techniques may also learn one or more transition parameters that, once satisfied or reached, may switch the radio communication unit from one radio state to another radio state. Using the detected radio state and the learned transition parameters, the client device can optimize network communications.

Abstract: The techniques described herein involve analysis of communication data included in trace file(s) of device(s) involved in a communication. These trace file(s) may each include data associated with multiple layers of a communication protocol stack of a respective device or data associated with a single such layer. The techniques may further involve one or more of determination of performance metrics associated with data at a specific layer of a specific device, correlation of the data between layers of a device, or correlation of data across multiple device(s) involved in the communication. The performance metrics or correlated data may then be analyzed based on thresholds or models to determine whether the performance metrics or correlated data exhibits a degraded quality of user experience. Also or instead, graphic or textual representations of the performance metrics or correlated data may be generated.

Abstract: The techniques described herein involve analysis of communication data included in trace file(s) of device(s) involved in a communication. These trace file(s) may each include data associated with multiple layers of a communication protocol stack of a respective device or data associated with a single such layer. The techniques may further involve one or more of determination of performance metrics associated with data at a specific layer of a specific device, correlation of the data between layers of a device, or correlation of data across multiple device(s) involved in the communication. The performance metrics or correlated data may then be analyzed based on thresholds or models to determine whether the performance metrics or correlated data exhibits a degraded quality of user experience. Also or instead, graphic or textual representations of the performance metrics or correlated data may be generated.

Abstract: The techniques described herein detect which one of multiple different radio states a radio communication unit of a client device is currently operating in. The techniques may also learn one or more transition parameters that, once satisfied or reached, may switch the radio communication unit from one radio state to another radio state. Using the detected radio state and the learned transition parameters, the client device can optimize network communications.

Abstract: The techniques described herein detect which one of multiple different radio states a radio communication unit of a client device is currently operating in. The techniques may also learn one or more transition parameters that, once satisfied or reached, may switch the radio communication unit from one radio state to another radio state. Using the detected radio state and the learned transition parameters, the client device can optimize network communications.

Abstract: The techniques described herein involve analysis of communication data included in trace file(s) of device(s) involved in a communication. These trace file(s) may each include data associated with multiple layers of a communication protocol stack of a respective device or data associated with a single such layer. The techniques may further involve one or more of determination of performance metrics associated with data at a specific layer of a specific device, correlation of the data between layers of a device, or correlation of data across multiple device(s) involved in the communication. The performance metrics or correlated data may then be analyzed based on thresholds or models to determine whether the performance metrics or correlated data exhibits a degraded quality of user experience. Also or instead, graphic or textual representations of the performance metrics or correlated data may be generated.

Abstract: The techniques described herein involve analysis of communication data included in trace file(s) of device(s) involved in a communication. These trace file(s) may each include data associated with multiple layers of a communication protocol stack of a respective device or data associated with a single such layer. The techniques may further involve one or more of determination of performance metrics associated with data at a specific layer of a specific device, correlation of the data between layers of a device, or correlation of data across multiple device(s) involved in the communication. The performance metrics or correlated data may then be analyzed based on thresholds or models to determine whether the performance metrics or correlated data exhibits a degraded quality of user experience. Also or instead, graphic or textual representations of the performance metrics or correlated data may be generated.

Abstract: The techniques described herein involve analysis of communication data included in trace file(s) of device(s) involved in a communication. These trace file(s) may each include data associated with multiple layers of a communication protocol stack of a respective device or data associated with a single such layer. The techniques may further involve one or more of determination of performance metrics associated with data at a specific layer of a specific device, correlation of the data between layers of a device, or correlation of data across multiple device(s) involved in the communication. The performance metrics or correlated data may then be analyzed based on thresholds or models to determine whether the performance metrics or correlated data exhibits a degraded quality of user experience. Also or instead, graphic or textual representations of the performance metrics or correlated data may be generated.

Abstract: The techniques described herein present opportunities for service providers and/or network providers to optimize the Quality of User Experience (QoE) for data services by determining, using a broader network-based approach, the root cause of problems causing a service degradation. To determine the root cause of the problems, the techniques may collect different trace files from multiple different nodes in the telecommunications network. Each trace file includes a log of trace identifiers for numerous different data packets that have been generated, received, transmitted, relayed, and/or routed via the node in the telecommunications network, and each trace file log entry may be associated with a timestamp. Once collected, the techniques may correlate the different trace files from the multiple different nodes to identify, using a broader network-based analysis, service optimization opportunities.

Abstract: The techniques described herein involve analysis of communication data included in trace file(s) of device(s) involved in a communication. These trace file(s) may each include data associated with multiple layers of a communication protocol stack of a respective device or data associated with a single such layer. The techniques may further involve one or more of determination of performance metrics associated with data at a specific layer of a specific device, correlation of the data between layers of a device, or correlation of data across multiple device(s) involved in the communication. The performance metrics or correlated data may then be analyzed based on thresholds or models to determine whether the performance metrics or correlated data exhibits a degraded quality of user experience. Also or instead, graphic or textual representations of the performance metrics or correlated data may be generated.

Abstract: The techniques described herein present opportunities for service providers and/or network providers to optimize the Quality of User Experience (QoE) for data services by determining, using a broader network-based approach, the root cause of problems causing a service degradation. To determine the root cause of the problems, the techniques may collect different trace files from multiple different nodes in the telecommunications network. Each trace file includes a log of trace identifiers for numerous different data packets that have been generated, received, transmitted, relayed, and/or routed via the node in the telecommunications network, and each trace file log entry may be associated with a timestamp. Once collected, the techniques may correlate the different trace files from the multiple different nodes to identify, using a broader network-based analysis, service optimization opportunities.

Abstract: The techniques described herein detect which one of multiple different radio states a radio communication unit of a client device is currently operating in. The techniques may also learn one or more transition parameters that, once satisfied or reached, may switch the radio communication unit from one radio state to another radio state. Using the detected radio state and the learned transition parameters, the client device can optimize network communications.