Abstract: Techniques for execution of multiple threads in a multithreaded computing programming environment are disclosed. The techniques are especially well suited for environments that use multilayered programming architecture where a higher layer can build on the functions provided by a lower layer where the delay time is an important consideration. In one aspect, the conceptual notion of a “Worker” effectively serves to represent the thread-specific execution context for a thread of execution (“thread”) in a multithreaded computing environment. Another aspect, provides the notion of an Exclusion Area (EA) as logical lock that serves to protect shared resources in a multithreaded environment. The combination of the worker and EA are used to provide a powerful framework that, among other things, allows minimizing of the delay time.

Abstract: Techniques for execution of multiple threads in a multithreaded computing programming environment are disclosed. The techniques are especially well suited for environments that use multilayered programming architecture where a higher layer can build on the functions provided by a lower layer where the delay time is an important consideration. In one aspect, the conceptual notion of a “Worker” effectively serves to represent the thread-specific execution context for a thread of execution (“thread”) in a multithreaded computing environment. Another aspect, provides the notion of an Exclusion Area (EA) as logical lock that serves to protect shared resources in a multithreaded environment. The combination of the worker and EA are used to provide a powerful framework that, among other things, allows minimizing of the delay time.

Abstract: A method of operating real-time middleware associated with at least one node of a data distribution system is provided. At least one pool of a plurality of fixed block size units of memory of the node is allocated (e.g., via an operating system call). Based on loan requests for dynamic memory elements on behalf of a user application executing on the node, an indication of at least one of the allocated fixed block size units to be lent is provided. A list of which allocated fixed block size units are being lent from the pool is maintained, including maintaining the list based on return requests, on behalf of the user application executing on the node, of fixed block size units of the pool. Substantially all of the dynamic memory elements of the real-time middleware associated with the node are provided from the at least one pool of allocated fixed block size units based on the loan requests on behalf of the user application.