Abstract
Data Flow is a natural paradigm representing distributed programs able to express data and control dependencies between composing nodes. Our work concentrates on periodic Data-Flow programs having Hard Real-Time constraints. We propose a model and a stringbased representation for a relevant class of Data-Flow programs and present a two-phase algorithm able to compute a schedule for a given set of programs to be executed. The first phase computes a feasible solution (mapping and time assignments) using a Simulated Annealing technique, the second phase takes the mapping as input and computes the optimal solution, in terms of resource allocation, using a recursive descent Quasi-Newton method.
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© 1996 Springer-Verlag Berlin Heidelberg
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Davoli, R., Tamburini, F., Giachini, L.A. (1996). Scheduling Data Flow programs in Hard Real-Time environments. In: Jonsson, B., Parrow, J. (eds) Formal Techniques in Real-Time and Fault-Tolerant Systems. FTRTFT 1996. Lecture Notes in Computer Science, vol 1135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61648-9_45
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DOI: https://doi.org/10.1007/3-540-61648-9_45
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