Journal of Parallel and Distributed Computing
On Satisfying Timing Constraints in Hard-Real-Time Systems
IEEE Transactions on Software Engineering
Energy efficient CMOS microprocessor design
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
Energy-Aware Partitioning for Multiprocessor Real-Time Systems
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Real-Time Systems: Scheduling, Analysis, and Verification
Real-Time Systems: Scheduling, Analysis, and Verification
IEEE Transactions on Parallel and Distributed Systems
Ant Colony Optimization
Partitioning Real-Time Tasks among Heterogeneous Multiprocessors
ICPP '04 Proceedings of the 2004 International Conference on Parallel Processing
Assigning real-time tasks to heterogeneous processors by applying ant colony optimization
Journal of Parallel and Distributed Computing
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Task assignment in a heterogeneous multiprocessor is a NP-hard problem, so approximate methods are used to solve the problem. In this paper the Modified Binary Particle Swarm Optimization (Modified BPSO) algorithm and Novel Binary Particle Swarm (Novel BPSO) Optimization are applied to solve the real-time task assignment in heterogeneous multiprocessor. The problem consists of a set of independent periodic task, which has to be assigned to a heterogeneous multiprocessor without exceeding the utilization bound. The objective is to schedule maximum number of tasks with minimum energy consumption. The execution times and deadlines of the tasks are assumed to be known. Here Modified BPSO performance is compared with Novel BPSO and Ant Colony Optimization algorithm (ACO). Experimental results show that Modified BPSO performs better than Novel BPSO and ACO for consistent utilization matrix and ACO performs better than Modified BPSO and Novel BPSO for inconsistent utilization matrix.