Abstract: Embodiments of the present invention may involve a method, system, and computer program product for controlling privacy in a face recognition application. A computer may receive an input including a face recognition query and a digital image of a face. The computer may identify a target user associated with a facial signature in a first database based at least in part on a statistical correlation between a detected facial signature and one or more facial signatures in the first database. The computer may extract a profile of the target user from a second database. The profile of the target user may include one or more privacy preferences. The computer may generate a customized profile of the target user. The customized profile may omit one or more elements of the profile of the target user based on the one or more privacy preferences and/or a current context.

Abstract: In at least one embodiment, a method and a system include a node potentially having information responsive to an information request distributed into, for example, a federated coalition network where the node receives at least one information request packet, conducts a search of information at the node to determine if requested information is present, when the requested information is present, then the node sends an acknowledgement to a requesting node, linear network codes the requested information into m packets where m is greater than or equal to k, which is the number of packets needed to be received by the requesting node to reconstruct the requested information, selects multiple paths between the node and the requesting node such that no third party will see more than k?1 different packets, and transmits the m packets distributed over the selected paths.

Abstract: The present disclosure relates generally to the field of migration (e.g., seamless migration) of a network connection under mobility (e.g., host mobility). In various examples, migration (e.g., seamless migration) of a network connection under mobility (e.g., host mobility) may be implemented in the form of methods and/or algorithms.

Abstract: The present disclosure relates generally to the field of migration (e.g., seamless migration) of a network connection under mobility (e.g., host mobility). In various examples, migration (e.g., seamless migration) of a network connection under mobility (e.g., host mobility) may be implemented in the form of systems and/or algorithms.

Abstract: The present disclosure relates generally to the field of migration (e.g., seamless migration) of a network connection under mobility (e.g., host mobility). In various examples, migration (e.g., seamless migration) of a network connection under mobility (e.g., host mobility) may be implemented in the form of methods and/or algorithms.

Abstract: The present disclosure relates generally to the field of logical movement of data objects. In various examples, the logical movement of data objects may reduce or eliminate network hotspots (e.g., avoid formation of hotspots, remove existing hotspots and/or reduce the magnitude of hotspots). In various examples, the logical movement of data objects may be implemented in the form of systems, methods and/or algorithms.

Abstract: Traffic redirection methods include determining a quality-affective factor comprising a quality-affective factor in an existing connection between a client and a server in a network. The quality-affective factor is compared to a threshold to determine whether the connection would benefit from a network processing function. A router is reconfigured to exclude the middlebox from the connection, if the connection would not benefit from the network processing function and if the middlebox is already present in the connection, to cease operation of the middlebox on the connection. The router reconfiguration is delayed until the connection is idle.

Abstract: Embodiments of the present invention may involve a method, system, and computer program product for controlling privacy in a face recognition application. A computer may receive an input including a face recognition query and a digital image of a face. The computer may identify a target user associated with a facial signature in a first database based at least in part on a statistical correlation between a detected facial signature and one or more facial signatures in the first database. The computer may extract a profile of the target user from a second database. The profile of the target user may include one or more privacy preferences. The computer may generate a customized profile of the target user. The customized profile may omit one or more elements of the profile of the target user based on the one or more privacy preferences and/or a current context.

Abstract: A middlebox includes a network monitor module configured to determine a quality-affective factor in a connection between a client and a server in a network. A processor is configured to compare the quality-affective factor to a threshold to determine whether the connection would benefit from a network processing function. A network control module is configured to configure a router to exclude the middlebox from the connection if the connection would not benefit from the network processing function and if the middlebox is already present in the connection to cease operation of the middlebox on the connection. Router configuration is delayed until the connection is idle.

Abstract: Traffic redirection methods include determining a quality-affective factor in a connection between a client and a server in a network; comparing the quality-affective factor to a threshold to determine whether the connection would benefit from a network processing function; reconfiguring the network to redirect the connection to or away from a middlebox that performs the network processing function in accordance with the determination of whether the connection would benefit from the network processing function.

Abstract: Dynamic middleboxes include a network monitor module configured to determine a quality-affective factor in a connection between a client and a server in a network; a processor configured to compare the quality-affective factor to a threshold to determine whether the connection would benefit from a network processing function; and a network control module configured to reconfigure the network to redirect the connection to a middlebox that performs the network processing function if the connection would benefit and further configured to reconfigure the network to exclude the middlebox from the connection if the connection would not benefit.

Abstract: In one embodiment, a computer-implemented method includes receiving a network graph describing a network having two or more nodes. An application graph is received describing a data stream application. The application graph includes one or more vertices, each corresponding to an operator of the application and associated with a list of nodes. A first vertex of the application graph corresponds to a first operator and is associated with two or more nodes. The application graph is augmented, which includes replicating the first operator such that the augmented graph includes a copy of the first operator at each of the nodes associated with the first vertex. The application is deployed over the network based on the augmented graph, such that a copy of the first operator is deployed at each of the nodes associated with the first vertex. A route through the augmented graph is selected for a data stream.

Abstract: The present disclosure relates generally to the field of logical movement of data objects. In various examples, the logical movement of data objects may reduce or eliminate network hotspots (e.g., avoid formation of hotspots, remove existing hotspots and/or reduce the magnitude of hotspots). In various examples, the logical movement of data objects may be implemented in the form of systems, methods and/or algorithms.

Abstract: In one embodiment, a computer-implemented method includes receiving a network graph describing a network having two or more nodes. An application graph is received describing a data stream application. The application graph includes one or more vertices, each corresponding to an operator of the application and associated with a list of nodes. A first vertex of the application graph corresponds to a first operator and is associated with two or more nodes. The application graph is augmented, which includes replicating the first operator such that the augmented graph includes a copy of the first operator at each of the nodes associated with the first vertex. The application is deployed over the network based on the augmented graph, such that a copy of the first operator is deployed at each of the nodes associated with the first vertex. A route through the augmented graph is selected for a data stream.

Abstract: The present disclosure relates generally to customer demographic information (e.g., monetizing customer demographic information). In various examples, obtaining, aggregating and/or providing customer demographic information may be implemented in the form of systems, methods and/or algorithms.

Abstract: The present disclosure relates generally to customer demographic information (e.g., monetizing customer demographic information). In various examples, obtaining, aggregating and/or providing customer demographic information may be implemented in the form of systems, methods and/or algorithms.

Abstract: Mechanisms are described to extract location information from unstructured text, comprising: building a language model from geo-tagged text; building a classifier for differentiating referred and physical location; given unstructured text, identifying referred location using the language model (that is, the location to which the unstructured text refers); given the unstructured text, identifying if referred location is also the physical location using the classifier; and predicting (that is, performing calculation(s) and/or estimation(s) of degree of confidence) of referred and physical location.

Abstract: The present disclosure relates generally to the field of proactive data object replication in named data networks. In various examples, proactive data object replication may be implemented in one or more named data networks in the form of systems, methods and/or algorithms.

Abstract: The present disclosure relates generally to the field of proactive data object replication in named data networks. In various examples, proactive data object replication may be implemented in one or more named data networks in the form of systems, methods and/or algorithms.

Abstract: Mechanisms are described to extract location information from unstructured text, comprising: building a language model from geo-tagged text; building a classifier for differentiating referred and physical location; given unstructured text, identifying referred location using the language model (that is, the location to which the unstructured text refers); given the unstructured text, identifying if referred location is also the physical location using the classifier; and predicting (that is, performing calculation(s) and/or estimation(s) of degree of confidence) of referred and physical location.