Genetic Programming for Dynamic Workflow Scheduling in Fog Computing
Author:
Affiliation:
1. Evolutionary Computation Research Group, School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand
2. Intelligent Robotics Research Center, Zhejiang Lab, Hangzhou, China
Funder
Marsden Fund of New Zealand
MBIE SSIF Fund
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Information Systems and Management,Computer Networks and Communications,Computer Science Applications,Hardware and Architecture
Link
http://xplorestaging.ieee.org/ielx7/4629386/10213383/10064120.pdf?arnumber=10064120
Reference66 articles.
1. Dynamic multi-workflow scheduling: A deadline and cost-aware approach for commercial clouds
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3. Achieving Flexible Scheduling of Heterogeneous Workflows in Cloud through a Genetic Programming Based Approach
4. Performance analysis of FCFS and improved FCFS scheduling algorithms for dynamic real-time computer systems
5. Integer linear programming-based multi-objective scheduling for scientific workflows in multi-cloud environments
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