Abstract:
Methods, systems, and apparatuses for privacy management comprise maintaining a database of subscriber data and subscriber consent rules associated with the subscriber data, receiving a consent request for selected subscriber data, determining a consent rule associated with the selected subscriber data, wherein the consent rule is determined based on user-type criteria, and transmitting a parameter associated with the selected subscriber data if the consent rule is satisfied.
Abstract:
Methods, systems, and apparatuses for selectively exposing subscriber data include maintaining subscriber data at a digital data storage, wherein the digital data storage is protected by a service provider firewall. A request to expose subscriber data from a third-party requestor is received. Selected subscriber data and a security condition associated with the request are determined, wherein the security condition is based on an identity of the third-party requestor. The selected subscriber data is retrieved if the security condition is satisfied, and the selected subscriber data is transmitted to the third-party requestor.
Abstract:
A controller function residing underneath a client application in a TCP/IP stack or session layer monitors state and status information associated with session-based application layer functions (e.g., content retrieval) and uses this information to migrate one or more sessions from a first client interface to a second client interface (e.g., 3G, 4G, LTE, 802.1 1x, WiMAX) and to a different application function serving entity (e.g., a different content server, cache server, service provider).
Abstract:
A predictive tracking method and apparatus utilizing objective and subjective data in order to predict user states is provided herein. For example, some such embodiments may allow a user to track their mood or health symptoms in relation to retrieved data regarding their environmental in order to reveal patterns that can help forecast and proactively manage mood or health symptoms.
Abstract:
Various exemplary embodiments relate to a method and related network node including one or more of the following: detecting, by a resource allocation device, a failure of server hardware; identifying a first agent device that is configured to utilize the server hardware; and taking at least one action to effect a reconfiguration of the first agent device in response to the server hardware failure. Various embodiments additionally include one or more of the folio wing: identifying a second agent device that is configured to utilize the server hardware; and taking at least one action to effect a reconfiguration of the second agent device in response to the server hardware failure. Various embodiments additionally include one or more of the following: receiving, by the resource allocation device from a second agent device, an indication of the failure of server hardware, wherein the second agent device is different from the first agent device.
Abstract:
In one aspect, an encoder comprises arbitrary precision multiple description generation circuitry configured to produce multiple descriptions of a given signal by processing the signal using at least one matrix having a dimension which is selected as a function of a designated number of transmission resources, such as OFDM subcarriers or TDM time slots, that are allocated for transmission of the multiple descriptions. For example, the signal may comprise a vector x of dimension N and the arbitrary precision multiple description generation circuitry may be configured to generate M descriptions of the vector x where the value of M is selected to satisfy a particular one of three possible cases M = N, M > N and M
Abstract:
A scalable voice signature authentication capability is provided herein. The scalable voice signature authentication capability enables authentication of varied services such as speaker identification (e.g. private banking and access to healthcare account records), voice signature as a password (e.g. secure access for remote services and document retrieval) and the Internet and its various services (e.g., online shopping), and the like.
Abstract:
An exemplary method of determining location information includes transmitting a modeling signal from each of a plurality of detectors. Each of the plurality of detectors receives at least one of the transmitted modeling signals from the other detectors. At least one characteristic of each of the received modeling signals is determined. A signal propagation model for an area near each of the detectors is automatically determined based on the characteristic of each of the received modeling signals. The determined propagation model indicates an effect on a signal received within the corresponding area.