Self-describing and data propagation model for data distribution service

Abstract. To realize real-time information sharing in generic platforms, it is especially important to support dynamic message structure changes. For the case of IDL, it is necessary to rewrite applications to change data sample structures. In this paper, we propose a dynamic reconfiguration scheme of data sample structures for DDS. Instead of using IDL, which is the static data sample structure model of DDS, we use a self describing model using data sample schema, as a dynamic data sample structure model to support dynamic reconfiguration of data sample structures. We also propose a data propagation model to provide data persistency in distributed environments. We guarantee persistency by transferring data samples through relay nodes to the receiving nodes, which have not participated in the data distribution network at the data sample distribution time. The proposed schemes can be utilized to support data sample structure changes during operation time and to provide data persistency in various environments, such as real-time enterprise environments and connection-less internet environments

Going Beyond Deadline-Driven Low-level Scheduling in Distributed Real-Time Computing Systems

Abstract: In real-time computing systems, timing-requirement specifications coming from the application designer are the obvious primary driver for resource allocation. Deadline-driven scheduling of computation-segments has been studied as an advanced mode of scheduling devised to meet the timing requirement specifications. However, it does not reflect additional concerns of the application designer, the damaging impacts of various timing violations on the application. The notion of risk-incursion function (RIF) as a framework for specification of such damaging impacts has been established by the first co-author. In this paper, a concrete implementation approach of the RIFdriven resource allocation scheme is discussed first. Then two RIF-based scheduling algorithms are discussed. The results of the experiment conducted to compare the performance of RIF-based scheduling algorithms against that of deadline-driven scheduling algorithms are also provided