Seven Networks, LLC

Aeris Communications, Inc.

Vivek Agarwal

Yuan Kang Lee

Chaitali Sengupta

Drew S Johnson

Eran Netanel

George Edward L Schaefer, Jr

Rony Gotesdyner

Sudipta Sen

Tejas Jukar

Subhakar Reddy Chedulla

Varun Sundharbabu

A computer-implemented method and system for optimizing user experience and power management are disclosed. The method includes determining power profile of a target device; determining historical behavior of at least one user in relation to the target device; considering the historical behavioral data of the at least one user in relation to the target device based on the determined power profile of the target device; using rules to select at least one of a plurality of approaches for establishing connection with a server in relation to a result of the considering; and establishing the connection with the target device based on the at least one of the plurality of approaches selected.

Method and system for optimizing execution of user commands in relation to power management

Techniques are disclosed for estimating a surrounding in which a mobile device is situated based on sensors of the mobile device. The sensors can be typical sensors currently existing on mobile devices and not dedicated for surrounding detection purposes. One embodiment includes a method which comprises retrieving a weather condition from a remote server; deriving, based on the weather condition, a plurality of weights for sensors on the mobile device; applying each weight to an output of a corresponding sensor on the mobile device; and determining whether the mobile device is likely to be indoor or outdoor based on one or more weighted outputs from the sensors. Among other advantages, embodiments disclosed herein increased accuracy to estimate the mobile device's surrounding without the need of dedicated sensors or other modification to mobile network infrastructures, thereby providing the benefit of surrounding sensing without incurring the cost.

Surrounding estimation based on sensors of a mobile device

In one embodiment, a method comprises measuring a set of parameters for each of the available networks using an application layer protocol (e.g., HTTP). The method further comprises determining an overall quality level for each of the available networks based on the parameters, and choosing the network based on the overall quality level. In some embodiments, the set of parameters are measured by communicating with each of a plurality of predetermined servers within a respective network. Among other advantages, embodiments disclosed herein enable a quantified approach to user experience estimation and application-level Quality of Experience (QoE) measurements, which can serve as bases for selection of radios for the applications.

Radio or network evaluation for selection based on measurements using application layer protocols at a mobile device

Techniques are disclosed for network and/or evaluation and selection based on received signal strength at a device. For example, an received signal strength indicator (RSSI) can be measured (e.g., using Android API or other suitable methods). Then, the measured RSSI level can be compared against a threshold RSSI level, which can be determined on a device-by-device basis. In some embodiments, the RSSI values can assist the network evaluation and selection in certain situations, for example, where WiFi network quality is degraded because of locational movement and not backbone structure, and/or where there are multiple access points (APs) providing WiFi networks under the same SSID and each AP having different effective coverage. Further, in some embodiments, the RSSI values can provide the capabilities of WiFi AP suspension based on MAC addresses. In some embodiments, the RSSI values can be adopted to trigger QoE measurements.

Quality of experience enhancement for wireless networks based on received signal strength at a mobile device

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Foster City, CA, United States of America

Vivek Agarwal