The Worst-Case Execution Time (WCET) analysis is an important stage in development process and verification of hard real-time systems. In this article the use of XML as a standard for exchanging timing information amongst timing analysis tools is proposed. Timing information resulted from automatic analysis of programs can be represented in XML format. Considering the type of information required for estimating the worst case execution time of programs, a set of XML tags is offered in this paper. Timing information resulted from analyzing a program by a timing analysis tool could be annotated within the program. The annotated code could be simply applied by other tools for relatively more accurate estimation of the worst case execution times. The paper also clears the way for future studies on using XML-based representation for extraction of information.
Worst-case execution time (WCET) analysis of a program is important to verify the temporal correctness of real-time systems. Parametric WCET analysis represents the WCET of the program as a formula, where the unknown values affecting the WCET are parameterized. Many issues usually affect the WCET of a program, including the loop bound. In parametric timing analysis, instead of determining a constant upper bound for a loop, a symbolic formula represents the loop bound. In this paper, a new method is presented for the parametric loop bound analysis based on path analysis. Instead of considering the basic bocks on their own and independent of the rest, the execution paths within the loop body have to be analyzed. There are certain situations in which the execution of certain statements of an execution path affects the number of executions of all the basic blocks along the execution path. Therefore, more accurate estimation of the number of loop iterations is provided. The results of analysis on the Mälardalen benchmark suite reveal the accuracy of the proposed method.
Fog computing is a promising paradigm for realtime and mission-critical Internet of Things (IoT) applications. Regarding the high distribution, heterogeneity, and limitation of fog resources, applications should be placed in a distributed manner to fully utilize these resources. In this paper, we propose a linear formulation for assuring the different availability requirements of application services while maximizing the utilization of fog resources. We also compare three multiobjective evolutionary algorithms, namely MOPSO, NSGA-II, and MOEA/D for a tradeoff between the mentioned optimization goals. The evaluation results in the iFogSim simulator demonstrate the efficiency of all three algorithms and a generally better behavior of MOPSO algorithm in terms of obtained objective values, application deadline satisfaction, and execution time.
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