Value vs. deadline scheduling in overload conditions

We present a comparative study among scheduling algorithms which use different priority assignments and different guarantee mechanisms to improve the performance of a real-time system during overload conditions. In order to enhance the quality of service, we assume that tasks are characterized not only by a deadline, but also by an importance value. The performance of the scheduling algorithm is then evaluated by computing the cumulative value gained on a task set, i.e. the sum of the values of those tasks that completed by their deadline. The purpose of this simulation study was twofold. Firstly, we wanted to discover which priority assignment is able to achieve the best performance in overload conditions. Secondly, we were interested in understanding how the pessimistic assumptions made in the guarantee test affect the performance of the scheduling algorithms, and how much a reclaiming mechanism can compensate this degradation. Simulation results show that, without any admission control, value-density scheduling performs best. Simple admission control based on worst case estimates of the load worsen the performance of all value based algorithms. EDF scheduling performs best if admission control is used along with a reclaiming mechanism that takes advantage of early completions. Finally, scheduling by deadline before overload and by value during overload works best in most practical conditions.