Genetic-Based Task Scheduling Algorithm with Dynamic Virtual Machine Generation in Cloud Computing
| Autor: | Farouk A. Emara, Kamal R. Raslan, Tamer A.A. Alzohairy, Ahmed A.A. Gad-ElRab |
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| Rok vydání: | 2021 |
| Předmět: |
Job shop scheduling
Computer Networks and Communications Heuristic (computer science) Computer science business.industry Distributed computing 020206 networking & telecommunications Cloud computing 02 engineering and technology Virtualization computer.software_genre Scheduling (computing) Task (computing) Hardware and Architecture Virtual machine Genetic algorithm 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) 020201 artificial intelligence & image processing business computer Software Information Systems |
| Zdroj: | International Journal of Computing. :165-174 |
| ISSN: | 2312-5381 1727-6209 |
| DOI: | 10.47839/ijc.20.2.2163 |
| Popis: | Recently, cloud computing has become the most common platform in the computing world. scheduling is one of the most important mechanism for managing cloud resources. Scheduling mechanism is a mechanism for scheduling user tasks among datacenters, host and virtual machines (VMs) and is an NP completeness problem. Most of existing mechanisms are heuristic and meta-heuristic methods, developed to address a part of scheduling problem and did not consider the dynamic creation of VMs by taking into account the required resources for a user task and the capabilities of a set of available hosts. To deal with this dynamic behavior, this paper introduces a new mechanism that uses a genetic algorithm (GA) for establishing a flexible scheduling mechanism that can adapt the dynamic number of VMs based on the required resources by user tasks and the available resources of hosts. Simulation results show that the proposed algorithm can distribute any number of user tasks on the available resources and it achieves better performance than existing algorithms in terms of response time, makespan, FlowTime, throughput, and resource utilization. |
| Databáze: | OpenAIRE |
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