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Task Scheduling using Modified PSO Algorithm in Cloud Computing Environment
| Content Provider | Semantic Scholar |
|---|---|
| Author | Abdi, Solmaz Motamedi, Seyyed Ahmad Sharifian, Saeed |
| Abstract | Task scheduling problem is one of the most important steps in using cloud computing environment capabilities. Different experiments show that although having an optimum solution is almost impossible but having a sub-optimal solution using heuristic algorithms seems possible. In this paper three heuristic approaches for task scheduling on cloud environment have been compared with each other. These approaches are PSO algorithm, genetic algorithm and modified PSO algorithm for efficient task scheduling. In all these three algorithms the goal is to generate an optimal schedule in order to minimize completion time of task execution. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://iieng.org/siteadmin/upload/3699E0114078.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Cloud computing Computation (action) Distributed computing Experiment Genetic algorithm Heuristic Job shop scheduling Makespan Merge Particle swarm optimization Phase-shift oscillator Schedule (computer science) Scheduling (computing) Scheduling - HL7 Publishing Domain Span Distance |
| Content Type | Text |
| Resource Type | Article |
