Systems and methods for predicting and preventing system incidents such as outages or failures based on advanced log analytics are described. A processing center comprising an incident prediction server and log database may receive application server logs generated by an application server and historical incident data generated by an incident database server. The processing center may be configured to cluster a subset of application server logs and based on the subset of application server logs and the incident data, determine in real time or near real time the likelihood of occurrence of an incident such as a system outage or failure.

Sessions in progress are seamlessly moved between devices of a software platform. Proximity-based session handovers are performed between devices of the software platform utilizing non-penetrating signals. The non-penetrating signals are detected by mobile devices. The non-penetrating signals include a frequency signature. The frequency signature is associated with a stationary device. A request to handover a session in progress from the mobile device to the stationary device is transmitted based on the detection of a non-penetrating signal. A handover of the session in progress from the mobile device to the stationary device is performed such that the session in progress is continued at the stationary device without interruption.

Sessions in progress are seamlessly moved between devices of a software platform. Proximity-based session handovers are performed between devices of the software platform utilizing short range signals. The short range signals include a frequency signature. The frequency signature is associated with a vehicle. A handover a session in progress from a mobile device to the vehicle is performed based on the detection of a short range signal.

A real-time streaming service predicts an incoming flash crowd event and manages computing resources to respond to the event before traffic peaks, thus reducing the likelihood that the streaming service's resources will be overwhelmed. Embodiments of a real-time streaming server predict a flash crowd event by detecting actions by client devices during a multi-step process to access a real-time content stream from an endpoint server cluster. Initially, the endpoint server has first computing resources configured to stream the content stream to the client devices. The streaming server provisions second computing resources at the endpoint server based on a rate at which the client devices perform an action associated with a first step in the multi-step process. The second computing resources are configured to stream the real-time content stream based on a rate at which the client devices perform an action associated with a second step in the multi-step process.

A real-time streaming service predicts an incoming flash crowd event and manages computing resources to respond to the event before traffic peaks, thus reducing the likelihood that the streaming service's resources will be overwhelmed. Embodiments of a real-time streaming server predict a flash crowd event by detecting actions by client devices during a multi-step process to access a real-time content stream from an endpoint server cluster. Initially, the endpoint server has first computing resources configured to stream the content stream to the client devices. The streaming server provisions second computing resources at the endpoint server based on a rate at which the client devices perform an action associated with a first step in the multi-step process. The second computing resources are configured to stream the real-time content stream based on a rate at which the client devices perform an action associated with a second step in the multi-step process.

Systems and methods for provisioning system components to execute jobs are provided. In one embodiment, a method is provided that includes receiving a request to provision system components for executing a job. Aggregate latencies for computing units may be calculated based on startup latencies for jobs executing on the computing units. A particular computing unit may be selected from among the plurality of computing units based on the aggregate latencies, and system components may be provisioned from the computing unit.

Systems and methods for provisioning system components to execute jobs are provided. In one embodiment, a method is provided that includes receiving a request to provision system components for executing a job. Aggregate latencies for computing units may be calculated based on startup latencies for jobs executing on the computing units. A particular computing unit may be selected from among the plurality of computing units based on the aggregate latencies, and system components may be provisioned from the computing unit.

Embodiments herein provide a method for CLAT Aware Affinity (CAA)-based scheduling by a user equipment (UE) (100) comprising a multi-core processor (120). The method includes a CAA scheduler (180) at the user equipment (100) receiving a packet and determining a path characteristic of the packet. Further, the method includes the CAA scheduler (180) determining, at least one of a IPv4 connection and a IPv6 connection based the path characteristic of the packet; and establishing a connection to at least one of an IPv4 server and an IPv6 server based on the determined at least one of the IPv4 connection and the IPv6 connection. Further, the method includes the CAA scheduler (180) classifying the packet into at least one class and scheduling the packet on at least one core of the multi-core processor (120) based on the at least one class.

Systems and methods are provided for the control of an industrial asset, such as a power generating asset. Accordingly, an interceptor module receives a state-change instruction from a state module that directs a change from a first state condition to a second state condition. The first and second state conditions direct modes of operation of at least one sub module of the controller of the industrial asset. The interceptor module then correlates the state-change instruction to a state-change classification. Based on the state-change classification, the interceptor module identifies an indication of a mode-switching attack. In response to the identification of the mode-switching attack, at least one mitigation response is implemented.

Techniques and structures to prevent exhaustion of a database connection pool, including receiving a plurality of events from a plurality of application servers operating as a database connection pool, categorizing each of the plurality of events, including generating a categorization message for each of the plurality events, wherein each categorization message includes one or more fields having contextual information to identify an event type to which an event is associated, analyzing the categorization messages to generate an event record; and generating a report based on the event record including one or more performance measurements to indicate an effectiveness of management of the database connection pool.