This paper presents a quantitative framework for early prediction of resource usage and load in distributed real-time systems (DRTS). The prediction is based on an analysis of UML 2.0 sequence diagrams, augmented with timing information, to extract timed-control flow information. It is aimed at improving the early predictability of a DRTS by offering a systematic approach to predict, at the design phase, system behavior in each time instant during its execution. Since behavioral models such as sequence diagrams are available in early design phases of the software life cycle, the framework enables resource analysis at a stage when design decisions are still easy to change. Though we provide a general framework, we use network traffic as an example resource type to illustrate how the approach is applied. We also indicate how usage and load analysis of other types of resources (e.g., CPU and memory) can be performed in a similar fashion. A case study illustrates the feasibility of the approach.
Abbreviations
ASAAutomatic system agent CCFG Concurrent control flow graph CCFP Concurrent control flow path CFP Control flow path DTCCFP Distributed timed concurrent control flow path LFQ Load forecasting query MBLF Model-based load forecasting MBPA Model-based predictability analysis MBRUA Model-based resource usage analysis NDD Network deployment diagram PA Predictability analysis DRTS Distributed real-time system RUA Resource usage analysis RUD Resource usage definition RUM Resource usage measure RUQ Resource usage query SCAPS SCAda-based power system SD Sequence diagram SDS Sequence diagrams schedule TC Tele-control unit TCCFP Timed concurrent control flow path UML-SPT UML profile for schedulability, performance, and time 123 276 V. Garousi et al.