Microsoft Technology Licensing, LLC

Weili Liu

Sharad Agarwal

Jyh-Han Lin

Xin Peng Liu

Sindhura Bandhakavi

Embodiments calculate an estimated latency between computing devices. A latency service aggregates latency records defining latency measurements and corresponding latency factors from a plurality of computing devices. From the aggregated latency records, the latency service defines relationships between the latency measurements and the corresponding latency factors. Responsive to a request for an estimated latency from a mobile computing device, the latency service applies the defined relationships to estimate the latency based on the latency factors associated with the received request. In some embodiments, the estimated latency includes three portions: a first latency value representing the latency from the mobile computing device to a cell site, a second latency value representing the latency from the cell site to an access point, and a third latency value representing the latency from the access point to a destination computing device.

Network latency estimation for mobile devices

A location-based service is provided that allows a user of a mobile device to tag and track the places he or she visits and share these places with social networking members. To implement this service a system receives location information from the user's location-aware mobile device over a wireless network. The location information identifies various locations or other points-of-interest that the user has visited. Based on this information the system determines a geographical domain that encompasses at least some of the locations the user has visited. Once a geographic domain has been determined it is presented to the user via the mobile device. The user is prompted to tag the geographical domain with an annotation that describes the geographic domain. The system stores the geographical domain and the annotation associated therewith so that it can be searched and accessed or retrieved by the user or members of the user's social network.

User-selected tags for annotating geographic domains containing points-of-interest

Embodiments analyze crowd-sourced data to identify a moved or moving beacon. The crowd-sourced data for the beacon is grouped into a plurality of clusters based on spatial distance. Timestamps associated with the crowd-sourced data in the clusters are compared to select one of the clusters. The crowd-sourced data associated with the selected cluster is used to determine position information for the beacon.

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Redmond, WA, United States of America

Weili Liu