Real-time task scheduling in heterogeneous multiprocessor systems using artificial bee colony

Scheduling of real-time tasks in multiprocessor systems is a NP-hard problem. Recently, swarm intelligence algorithms have been efficiently applied for this problem. Real-time tasks can be classified into hard real-time tasks and soft real-time tasks. The aim of hard real-time task scheduling algorithms is to meet all tasks deadline constraints. However, slight violation is not critical, in the case of soft real-time tasks. In this paper, a new algorithm based on artificial bee colony (ABC) is proposed for scheduling of soft real-time tasks. In this method, a hybrid neighborhood search mechanism is introduced to improve the convergence of ABC. Experimental results demonstrate the effectiveness of proposed algorithm for scheduling of soft realtime tasks in heterogeneous multiprocessor systems.