Abstract: A method and technique for link optimization for callout request messages includes monitoring one or more time-based parameters for each of a plurality of links between a communication pipe of a host system and one or more service systems. The links are used to send callout request messages between one or more applications running on the host system and the one or more service systems that process the callout request messages. The one or more time-based parameters are associated with different stages of callout request message processing by the communication pipe and the one or more service systems. The method also includes creating control data based on values of the one or more time-based parameters, creating the callout request messages to include the control data, and distributing the callout request messages to the one or more service systems via the links.

Abstract: A method and technique for link optimization for callout request messages includes monitoring one or more time-based parameters for each of a plurality of links between a communication pipe of a host system and one or more service systems. The links are used to send callout request messages between one or more applications running on the host system and the one or more service systems that process the callout request messages. The one or more time-based parameters are associated with different stages of callout request message processing by the communication pipe and the one or more service systems. The method also includes creating control data based on values of the one or more time-based parameters, creating the callout request messages to include the control data, and distributing the callout request messages to the one or more service systems via the links.

Abstract: A method and technique for link optimization for callout request messages includes monitoring one or more time-based parameters for each of a plurality of links between a communication pipe of a host system and one or more service systems. The links are used to send callout request messages between one or more applications running on the host system and the one or more service systems that process the callout request messages. The one or more time-based parameters are associated with different stages of callout request message processing by the communication pipe and the one or more service systems. The method also includes creating control data based on values of the one or more time-based parameters, creating the callout request messages to include the control data, and distributing the callout request messages to the one or more service systems via the links.

Abstract: A method and technique for link optimization for callout request messages includes monitoring one or more time-based parameters for each of a plurality of links between a communication pipe of a host system and one or more service systems. The links are used to send callout request messages between one or more applications running on the host system and the one or more service systems that process the callout request messages. The one or more time-based parameters are associated with different stages of callout request message processing by the communication pipe and the one or more service systems. The method also includes creating control data based on values of the one or more time-based parameters, creating the callout request messages to include the control data, and distributing the callout request messages to the one or more service systems via the links.

Abstract: According to one aspect of the present disclosure, a method and technique for link optimization for callout request messages is disclosed. The method includes: monitoring a plurality of different time-based parameters for each of a plurality of links between a communication pipe of a host system and one or more service systems, the links used to send and receive callout request messages between one or more applications running on the host system and the services systems that process the callout request messages, the time-based parameters associated with different stages of callout request message processing by the communication pipe and the service systems; assessing a performance level of each of the plurality of links based on the time-based parameters; and dynamically distributing the callout request messages to select links of the plurality of links based on the performance assessment.

Abstract: Techniques are disclosed to transmit arbitrarily large data units for transaction processing in a networked environment. A request is received to store a data unit of a size exceeding an allocated memory address space of a transaction gateway component of the networked environment. A predefined store function, provided by a repository interface component, is invoked to store the data unit to a data repository component of the networked environment and without segmenting the data unit. A repository handle of the stored data unit is identified. A predefined load function, provided by the repository interface component, is invoked to load a portion of the stored data unit, based on the identified repository handle, where the portion is smaller than the stored data unit.

Abstract: Techniques are disclosed to transmit arbitrarily large data units for transaction processing in a networked environment. A request is received to store a data unit of a size exceeding an allocated memory address space of a transaction gateway component of the networked environment. A predefined store function, provided by a repository interface component, is invoked to store the data unit to a data repository component of the networked environment and without segmenting the data unit. A repository handle of the stored data unit is identified. A predefined load function, provided by the repository interface component, is invoked to load a portion of the stored data unit, based on the identified repository handle, where the portion is smaller than the stored data unit.

Abstract: Techniques are disclosed to transmit arbitrarily large data units for transaction processing in a networked environment. A request is received to store a data unit of a size exceeding an allocated memory address space of a transaction gateway component of the networked environment. A predefined store function, provided by a repository interface component, is invoked to store the data unit to a data repository component of the networked environment and without segmenting the data unit. A repository handle of the stored data unit is identified. A predefined load function, provided by the repository interface component, is invoked to load a portion of the stored data unit, based on the identified repository handle, where the portion is smaller than the stored data unit.

Abstract: According to one aspect of the present disclosure, a method and technique for link optimization for callout request messages is disclosed. The method includes: monitoring a plurality of different time-based parameters for each of a plurality of links between a communication pipe of a host system and one or more service systems, the links used to send and receive callout request messages between one or more applications running on the host system and the services systems that process the callout request messages, the time-based parameters associated with different stages of callout request message processing by the communication pipe and the service systems; assessing a performance level of each of the plurality of links based on the time-based parameters; and dynamically distributing the callout request messages to select links of the plurality of links based on the performance assessment.

Abstract: Disclosed is an exemplary multiple hypothesis engine that provides situation assessment capabilities regarding cyber auto tactics techniques and procedures. Dynamic cyber adversarial operations are evaluated via a combination of techniques using a Bayesian multiple hypothesis tree, or graph, as a framework. A top-down probability propagation mechanism solves different aspects of the problem in a round-robin fashion. The top-down probability propagation mechanism comprises the Hypothesis Refinement Engine. A model-based abductive reasoner comprising The Hypothesis Validator is used to confirm or refute the refined hypothesis. A model-based learning engine comprising Behavior Model Trainer is used to incrementally augment the knowledge base of behavior models as new adversarial TTPs are discovered. These three techniques behave in a cooperative manner by operating upon the Bayesian multiple hypothesis tree framework.