A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues

By Yuming Xu, Kenli Li, Jingtong Hu, Keqin Li. Information Sciences, 2014

385 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Industrial and Manufacturing Engineering, Information Systems

View Paper: https://www.semanticscholar.org/paper/aaeeafed0b774392d5fbec3d25ec32d830a411bb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Shui Yu
2. D. Manjula
3. Vijayan Sugumaran
4. A. Arunarani

In Information Systems

1. Shui Yu
2. D. Manjula
3. Vijayan Sugumaran
4. A. Arunarani

Citations in the corpus

• Genetic algorithms: theory, genetic operators, solutions, and applications (2023, neutral): “Xu et al. [76] proposed a GA-based scheduling technique to find the optimal task schedule of heterogeneous computing systems depending on multiple priority queues.”
• Task scheduling techniques in cloud computing: A literature survey (2019, background): “[45] propositioned a genetic algorithm for task scheduling on heterogeneous computing systems by means of multiple priority queues (MPQGA).”
• A Parallel Random Forest Algorithm for Big Data in a Spark Cloud Computing Environment (2017, background): “Finally, Section 6 presents a conclusion and future work.”