Multi-Objective Task Scheduling Optimization in Cloud Computing: An Appraisal
Numerous task scheduling problems encountered in cloud computing (CC) environment cannot actually be formulated as a mono-objective problem. Hence, metaheuristic multi-objective (MO) scheduling algorithms are now being proposed to be a potential solution. This appraisal investigated
the existing MO task scheduling algorithms that optimize task scheduling in Infrastructure as a Service (IaaS) cloud. However, task scheduling algorithms are drawn from journals and conference proceedings for analysis. Performance metrics for cloud task scheduling were used to evaluate the
quality of performance attributes addressed by these algorithms. The percentage of MO Quality of Service (QoS) attributes (Execution cost/Energy consumption 5%, Response time/throughput 5%, Execution time/cost 40%, Execution time/Load balancing 5%, Execution time/Energy consumption 10%, Execution
cost/Makespan 25%, Execution time/Response time 5%, Execution cost, Makespan, Energy consumption/Fault tolerance 5%) addressed by existing algorithms is reported, while comparison based on experimental tools (ClodSim 42%, Matlab 33%, GridSim 10%, Wien2k and AstroGrid 5%, Java 5%, MetteroAG
5%) as used by the existing researchers were also reported. Percentage results showed, most existing MO scheduling algorithms minimized QoS attributes like task execution time, cost, and makespan without emphases on the scalability, reliability, energy consumption and fault tolerance. With
the adopted method for evaluating the existing algorithms, findings of this research will help researchers with further research directions on how to analyze different techniques pointing at the main research problem.
Keywords: Cloud Computing; Multi-Objective; Tasks Scheduling Optimization
Document Type: Research Article
Affiliations: Department of Computer Science, Faculty of Computing, Universiti Teknologi Malaysia, Johor, 81310, Malaysia
Publication date: 01 May 2018
- ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
- Editorial Board
- Information for Authors
- Subscribe to this Title
- Ingenta Connect is not responsible for the content or availability of external websites
- Access Key
- Free content
- Partial Free content
- New content
- Open access content
- Partial Open access content
- Subscribed content
- Partial Subscribed content
- Free trial content