IEEE Transactions on Parallel and Distributed Systems
On Exploiting Task Duplication in Parallel Program Scheduling
IEEE Transactions on Parallel and Distributed Systems
Genetic Scheduling for Parallel Processor Systems: Comparative Studies and Performance Issues
IEEE Transactions on Parallel and Distributed Systems
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Observations on Using Genetic Algorithms for Dynamic Load-Balancing
IEEE Transactions on Parallel and Distributed Systems
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
Hypertool: A Programming Aid for Message-Passing Systems
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
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Efficient task scheduling is essential for obtaining high performance in heterogeneous distributed computing systems (or HeDCSs). Because of its key importance, several scheduling algorithms have been proposed in the literature, which are mainly for homogeneous processors. Few scheduling algorithms are developed for HeDCSs. In this paper, we present a novel task scheduling algorithm, called the Longest Dynamic Critical Path (LDCP) Algorithm, for HeDCSs. The LDCP algorithm is a list-based scheduling algorithm that uses a new attribute to effectively compute the priorities of tasks in HeDCSs. At each scheduling step, the LDCP algorithm selects the task with the highest priority and assigns the selected task to the processor that minimizes its finish execution time using an insertion-based scheduling policy. The LDCP algorithm successfully generates task schedules that outperform, to the best of our knowledge, two of the best scheduling algorithms for HeDCSs.