Abstract:

A real-time aperiodic task overload handling mechanism based on value of task is presented in this paper. A method of verifying task overload is first presented. A mathematical model termed dynamic constraint knapsack model is established by combining two parameters, deadline and value of task. An enhanced dynamic greed algorithm (EDGA) is then presented to handle the model. By determining parameters and the value function of tasks, performance of EDGA is analyzed in terms of hit value ratio. Experimental results show that EDGA can
achieve higher hit value ratio compared to the earliest deadline first (EDF), highest value first (HVF) and robust
highest value first (RHVF) algorithms under all workload conditions.

Key words: real-time tasks overload, aperiodic task, dynamic knapsack, greedy algorithm