### Update on Overleaf.

parent 8d9cce12
 ... ... @@ -97,7 +97,7 @@ It is is optimal in sense of feasibility (it minimizes the maximum lateness unde worst case finishing time of task i: $f_i = t + \sum_{k=1}^i c_k(t)$ \\ EDF guarantee condition: $\forall i = 1,\dots ,n \quad t + \sum_{k=1}^i c_k(t)\leq d_i$ \begin{python} Algorithm: EDF_guarantee (set of jobs $J$, job $j_{new}$) Algorithm: EDF_guarantee (set of jobs $J$ ready at time t, job $j_{new}$ arriving at t) { $J'$ = $J \cup \{j_{new}\}$; /*ordered by deadline*/ $t$ = current_time(); ... ... @@ -108,6 +108,8 @@ EDF guarantee condition: $\forall i = 1,\dots ,n \quad t + \sum_{k=1}^i c_k(t)\l } return(FEASIBLE); } /*do this algorithm for every time instance where a new task arrives.*/ \end{python} A new task is accepted if the schedule remains feasible. \newline ... ...  ... ... @@ -89,6 +89,7 @@ ES are expected to finish tasks reliably within time bounds.\\ Essential: Upper \item$C_i$: WCET of task$i\$ \end{itemize} \includegraphics[width=0.6\linewidth]{symbols_cyclic_exec_scheduler} \\ \textbf{Conditions}: \\ \begin{tabularx}{\columnwidth}{|X|X|} \hline ... ...
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