A Hybrid Task Scheduling Approach Based on Genetic Algorithm and Particle Swarm Optimization Technique in Cloud Environment

  • Bappaditya Jana
  • Jayanta Poray
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 695)


As per current trends, cloud services are becoming more popular day by day. Because these services satisfy several demands for heterogeneous resources without using dedicated IT infrastructure. In cloud platform, user gets shared pool of resources through Internet irrespective of any geographical location. But cloud services need to handle a gigantic amount of request, as the number of users increases exponentially. In order to manage a pool of requests till now no effective scheduling mechanism is available in practice. So to minimize the time delay and optimize the overall complexity, suitable scheduling methodology is very much required. In our study, we have presented a novel scheme for scheduling algorithm after the enhancement of genetic algorithm and particle swarm optimization technique. We have proposed a methodology that can provide a better response time from cloud provider and minimize the waiting time for particular clients in cloud environment.


Cloud computing Genetic algorithm Max–min scheduling Min execution time Scheduling algorithm Particle swarm optimization Hybrid task scheduling algorithm Time hybrid task scheduling 


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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science & EngineeringTechno India UniversityKolkataIndia

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