Abstract: A stream server manages connections by multiple clients. The stream server receives, sends and manages streams for each client. The stream server analyzes incoming streams and maintains a database of device signatures and a database of user profiles based on the analyzed data. The stream server receives a stream from a client, analyzes the stream to identify an applicable device signature, user profile, or both, and modifies the stream. Modification of the stream may include filtering noise, placing the user in receive-only mode, ending a session for a user, adjusting metadata, etc. In addition, modification of the stream may vary based on the role or authorization of the user, or based on commands from one or more of the users.

Abstract: Sharing data among computing systems can include receiving, using a processor, a data transfer event indicating a transfer of a data file from a source system to a target system, querying, using the processor, the source system for an operating system executed by the source system and a file type of the data file, and querying, using the processor, the target system for an operating system executed by the target system. A target application can be determined using the processor. The target application is adapted for execution on the operating system executed by the target system and is adapted for operating on the file type. Installation of the target application on the target system can be initiated. Further, transfer of the data file from the source system to the target system can be initiated using the processor.

Abstract: A plurality of tuple values of a stream of tuples is gathered. A normal operating range of the stream of tuples is determined. The normal operating range includes essentially all expected values of the stream of tuples. An outlier value which is outside of the normal operating range is identified. The outlier value is injected into the stream of tuples as an outlier tuple. A reaction to the injection of the outlier tuple is detected and recorded.

Abstract: Improvements in data security and privacy may be realized by receiving a service request including a social range and a requestor identity; mining a first social network to create a social graph of entities within the social range of the requestor identity, wherein the entities are represented by nodes in the social graph linked to a requestor via one or more edges, wherein a number of edges used to link a given entity to the requestor does not exceed the social range; determining whether the social graph includes at least one person matching personnel included in an organizational chart; and in response to determining that the social graph includes no persons matching the personnel included in the organizational chart, transmitting an acceptance response from a provider-side system to a client-side system.

Abstract: Provided are techniques for operator isolation based on data security requirements. At a cloud node, a graph is received that includes ingest portions of data and operators. For each of the operators, it is determined whether the operator processes protected data. In response to determining that the operator is tagged with an indication that the operator processes protected data, the operator is forwarded to a tenant secure node for processing. In response to determining that the operator is not tagged with an indication that the operator processes protected data, the operator is forwarded to a tenant general node for processing. Then, while the tenant general node is processing the operator, in response to determining that the operator is processing protected data a tag is associated with the operator to indicate that the operator processes protected data and the operator is forwarded to the tenant secure node for processing.

Abstract: A stream server manages connections by multiple clients. The stream server receives, sends and manages streams for each client. The stream server analyzes incoming streams and maintains a database of device signatures and a database of user profiles based on the analyzed data. The stream server receives a stream from a client, analyzes the stream to identify an applicable device signature, user profile, or both, and modifies the stream. Modification of the stream may include filtering noise, placing the user in receive-only mode, ending a session for a user, adjusting metadata, etc. In addition, modification of the stream may vary based on the role or authorization of the user, or based on commands from one or more of the users.

Abstract: Embodiments of the present invention provides methods, computer program products, and a system for determining a set of potential responders to alert a second party regarding an urgent communication. Embodiments of the present invention can be used to determine if a missed communication placed by a first party to a second party is an urgent communication. Embodiments of the present invention can be used to determine a set of potential responders based, at least in part, on a variety of possible locations of a communication device belonging to the second party.

Abstract: System resource usage by a streaming application processing workloads can be monitored. Based on the monitoring, at least one performance metric for the streaming application in processing the workloads can be determined. Based on the at least one performance metric, whether hosting of the streaming application is, or is near to, violating at least one criteria specified by a service level agreement for the streaming application can be determined. If so, at least one additional instance of at least one parallelizable operator of the streaming application that is currently executing can be initialized. Responsive to initializing the at least one additional instance of at least one of the parallelizable operators, a portion of the workloads can be directed to the at least one additional instance of at least one of the parallelizable operators.

Abstract: A method, computer program product, and computing device for monitoring network activity associated with streaming a data load through a stream application including a plurality of stream operators deployed on a plurality of computing devices. One or more stream operators with one or more external connections may be identified from the plurality of stream operators. The identified one or more stream operators may be deployed based upon, at least in part, the one or more external connections.

Abstract: A method, apparatus and program product utilize Domain Name Service (DNS) prefetching in a recursive DNS server, e.g., to mitigate Distributed Denial of Service (DDoS) attacks on a DNS service.

Abstract: A method, apparatus and program product utilize Domain Name Service (DNS) prefetching in a recursive DNS server, e.g., to mitigate Distributed Denial of Service (DDoS) attacks on a DNS service.

Abstract: Disclosed aspects relate to resource usage management in a stream computing environment that includes a set of hosts having a set of processing elements which has a set of stream operators. A first activity indicator may be detected for a first subset of the set of stream operators. A resource action for performance with respect to the first subset of the set of stream operators may be determined based on the first activity indicator. The resource action may be performed with respect to the first subset of the set of stream operators to benefit resource usage in the stream computing environment.

Abstract: A plurality of tuple values of a stream of tuples is gathered. A normal operating range of the stream of tuples is determined. The normal operating range includes essentially all expected values of the stream of tuples. An outlier value which is outside of the normal operating range is identified. The outlier value is injected into the stream of tuples as an outlier tuple. A reaction to the injection of the outlier tuple is detected and recorded.

Abstract: A computer-implemented method, in an example, may include calculating a time-to-live value for at least one packet based on a hop count between each of a plurality of processing element containers within an application streaming network; updating at least one processing element container output connection based on the calculated time-to-live value; and monitoring a streams resource metrics service for a change in a packet delivery rate.

Abstract: A mechanism is provided for automated management of a set of media data using a set of social networking data. The set of social networking data related to a media event is collected. The set of social networking data related to the media event is correlated with the set of media data of the media event. Based on the set of social networking data, a determination is made of an inflection point of the media event. An inflection marker for the inflection point of the media event is then established with respect to the set of media data of the media event.

Abstract: A method and system are provided. The method includes automatically monitoring one or more voice communication sessions occurring on multiple communication devices to transcribe into text, by a processor-based voice-to-text transcriber, voices uttered by two or more respective participants other than a user in each of the voice communications sessions. The method further includes comparing, for each of the voice communication sessions, the topic of interest to conversation features derived from the text to detect a match there between. The method also includes providing the user with a summary of each of the voice communication sessions for which the match has been detected by said comparing step, the summary being based on the text. The method additionally includes automatically connecting the user to at least one of the voice communication sessions for which the summary thereof has been provided to the user.

Abstract: A computer-implemented method, in an example, may include calculating a time-to-live value for at least one packet based on a hop count between each of a plurality of processing element containers within an application streaming network; updating at least one processing element container output connection based on the calculated time-to-live value; and monitoring a streams resource metrics service for a change in a packet delivery rate.

Abstract: A writing style of content of a composed message, directed to a set of recipients, may be determined. A previous message that includes a first subset of recipients in the set of recipients may be analyzed. Writing habits of the first subset of recipients may be identified based on the analyzing. A difference between the writing style of the content and the writing habits of the first subset of recipients may be identified. The content of the composed message may be modified based on the difference.

Abstract: In using a virtual extensible local area network (VXLAN) for stream processing, a management system allocates resources for a streaming application based on an operator graph of the streaming application. The management system assigns the resources to a group of VXLAN segments based on the operator graph of the streaming application. A first processing element of the streaming application multicasts data on the group of VXLAN segments. A second processing element on a given VXLAN segment of the group of VXLAN segments receives the data. If the second processing element is an intended recipient of the data, then the second processing element processes the data. If the second processing element is not the intended recipient of the data, then the second processing element ignores the data.

Abstract: A stream of tuples to be processed by a plurality processing elements executing on two or more compute nodes is received. Each compute node stores one or more of the processing elements having one or more stream operators. It is determined whether an overhead parameter associated with a first streams service located at a first stream operator is outside of a first overhead criterion. The first streams service is ended at the first stream operator and a second streams service is instantiated at a second stream operator when the overhead parameter associated with the first streams service is outside of the first overhead criterion. The second stream operator is different from the first stream operator. The method may include determining whether the first streams service samples a first data attribute of tuples or measures performance.