Scheduling an overloaded real-time system

The real-time systems differ from the conventional systems in that every task in the real-time system has a timing constraint. Failure to execute the tasks under the timing constraints may result in fatal errors. Sometimes, it may be impossible to execute all the tasks in the task set under their timing constraints. Considering a system with limited resources, one solution to handle the overload problem is to reject some of the tasks in order to generate a feasible schedule for the rest. In this paper, we consider the problem of scheduling a set of tasks without preemption in which each task is assigned criticality and weight. The goal is to generate an optimal schedule such that all of the critical tasks are scheduled and then the non-critical tasks are included so that the weight of rejected non-critical tasks is minimized. We consider the problem of finding the optimal schedule in two steps. First, we select a permutation sequence of the task set. Secondly, a pseudopolynomial algorithm is proposed to generate an optimal schedule for the permutation sequence. If the global optimal is desired, all permutation sequences have to be considered. Instead, we propose to incorporate the simulated annealing technique to deal with the large search space. Our experimental results show that our algorithm is able to generate near optimal schedules for the task sets in most cases while considering only a limited number of permutations.